MOHNYIN TOWNSHIP” · 2012. 11. 13. · iv SUMMARY The Indawgyi lake area, located in the north-west of Myanmar is a wetland area and one of the largest freshwater reservoirs of

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"SOCIO – ECONOMIC ANALYSIS OF THE INDAWGYI LAKE AREA,

MOHNYIN TOWNSHIP”

A Thesis

Submitted to the Examination Committee of the International Master of

Environmental Science Program

University of Cologne

In partial fulfilment of the requirements for

The degree of Master of Environmental Science

By

Zin Mar Than

September 2011

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Copyright by

Zin Mar Than

2011

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"SOCIO – ECONOMIC ANALYSIS OF THE INDAWGYI LAKE AREA,

MOHNYIN TOWNSHIP”

By

Zin Mar Than

September 2011

Thesis supervised by Professor Frauke Kraas

Professor Josef Nipper

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SUMMARY

The Indawgyi lake area, located in the north-west of Myanmar is a wetland area and one of

the largest freshwater reservoirs of the country. It is heritage to rich and manifold natural

treasures in fauna and flora. It was declared a protected area as Bird Sanctuary in 1999.

At the same time it is rather densely populated due to comparatively attractive living

circumstances, supported, besides others, by the rich aquatic and bird life.

However, only limited information about the present socio-economic situation of the

inhabitants is available, due to poor administrative structures in the region and the lack of

awareness from the central government, which is engaged to administrate other issues,

which Myanmar has more than enough to counter.

These facts and the growing importance of a sustainable development in today´s globalized

environment have formed the concept for this study.

The aim was to collect information about the present socio-economic situation of the

Indawgyi lake area, necessary for a risk assessment.

Besides literature studies at the Universities of Yangon, Myitkyina and Mohnyin Degree

College, information was contributed from associates of the forest ministry and from the

park wardens on site.

Personal, semi-structured interviews, conducted in the area, and observations to gain recent

data have been accomplished with 100 randomly selected families, representing 536

inhabitants of the area. Those families lived in 5 villages within the survey area, namely

Sweletpan, Mamonkaing, Hepa, Nyaungbin and Lonton. The questionnaire was set up to

deliver data for three categories.

1. Social factors, like family size, gender distribution, homestead types, residence

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time, educational status, access to health care facilities,… to education facilities,

availability of transportation and communication.

2. Economic factors, like source(s) of income, land- / livestock- ownership, annual

expenditures,

3. Socio- Economic risks to the environment and sustainable eco system services like

firewood consumption, water and soil pollution, fishing behaviour – (overfishing),

hunting practices.

The results were categorized and analysed to determine socioeconomic and ecological

differences between individuals, locations and occupations.

No distinct correlation between occupation and income was found. Family size proved to

be the main determent, whether individuals incomes are below or above the World Bank

defined poverty line. Most homes were frugal; a considerable share of interviewees lived on

boat homes. Healthcare was clearly defined as an issue, so were transportation and

communication. Education offerings were found acceptable.

Earn of livelihood often needs more than one occupation and in many cases is unsecure,

due to business sizes, property and livestock ownerships and lack of knowledge. Some of

the respondents had to invest, so their spending exceeded their incomes. Fishing has been

found as main income source. Shrinking Fish population caused by manifold reasons

(overfishing, pollution, disregard of closed season) is a threat.

Bird hunting practices by poisoning is another one, as it endangers not only the bird

population of the protected sanctuary, but also directly the health of those who ingest them.

Mercury pollution is another risk factor which needs to be controlled by more strict

regulations and surveillance.

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ACKNOWLEDGEMENT

I want to express my deepest gratitude to F.E.S for supporting and providing me the

opportunity to study in Germany.

I would like to express my heartfelt thanks to Prof. Frauke Kraas, as a supervisor who

inspired me to initiate this research program.

My deepest appreciation is rendered to Prof. Josef Nipper for his supervision and

contribution on my thesis.

My warmest thanks are also extended to Dr. Regine Spohner and Dr. Verena Dlugloß for

their kind help in making my water analysis possible.

I owe a deep gratitude for the respondents who kindly spend their times for the interviews

and provided me with valuable data.

Especially heartfelt thanks are extended to all staffs of Indawgyi Wildlife Sanctuary, Nature

and wildlife Conservation Division Mohnyin Township (Ministry of Forestry) and Indo-

Myanmar Conservation (NGO). Without their support it would not have been a successful

job.

Thanks are also extended to my colleagues, friends especially those who helped to get the

resources and the contacts for field research.

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TABLE OF CONTENTS

SUMMARY ..............................................................................................................................iv

ACKNOWLEDGEMENT.........................................................................................................vi

LIST OF TABLES ..................................................................................................................... x

LIST OF FIGURES ................................................................................................................. xii

LIST OF PLATES................................................................................................................ xiiiii

LIST OF ABBREVIATIONS ................................................................................................. xiv

CHAPTER 1: INTRODUCTION ........................................................................................ 1

1.1 The aims of the study ........................................................................................................... 2

1.2 General description of the Indawgyi lake area .................................................................... 2

1.2.1 Topography and drainage .................................................................................................. 2

1.2.2 Climate and soil ................................................................................................................. 3

1.2.3 Vegetation and land cover ................................................................................................. 4

1.3 Challenges for Indawgyi lake ............................................................................................... 4

1.3.1 Overfishing ........................................................................................................................ 4

1.3.2 Land use management ....................................................................................................... 5

1.3.3 Gold mining ...................................................................................................................... 6

(i) Method .................................................................................................................................. 6

(ii) Emission of mercury in the environment .............................................................................. 7

(iii) Mercury in fish .................................................................................................................... 7

(iv) Human exposure pathways and health effects ..................................................................... 8

(v) Ecological effects of mercury ............................................................................................... 8

1.3.4 Firewood consumption ...................................................................................................... 9

1.3.5 Waste disposal ................................................................................................................... 9

1.3.6 Hunting............................................................................................................................ 11

1.3.7 Institutional management ................................................................................................ 11

CHAPTER 2: REVIEW OF LITERATURE ..................................................................... 17

2.1 Socioeconomic aspects ....................................................................................................... 17

2.2 Environment aspects........................................................................................................... 20

CHAPTER 3: MATERIALS AND METHODS ..................................................................... 23

3.1 Study area ........................................................................................................................... 23

3.2 Interview-based survey ....................................................................................................... 23

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3.3 Recording of fish species and fishing gear ......................................................................... 24

3.4 Recording of environmental data........................................................................................ 24

CHAPTER 4: RESULTS ........................................................................................................ 26

4.1 Social Factors ..................................................................................................................... 26

4.1.1 Population and settlement trend....................................................................................... 26

4.1.2 Age groups and gender .................................................................................................... 27

4.1.3 Working classes............................................................................................................... 28

4.1.4 Education and health ....................................................................................................... 29

4.1.5 House structures .............................................................................................................. 30

4.1.6 Electric power supply ...................................................................................................... 31

4.1.7 Water supply ................................................................................................................... 32

4.1.8 Transportation and communication ................................................................................. 33

4.2 Economic Factors ............................................................................................................... 35

4.2.1 Fishery sector .................................................................................................................. 35

4.2.2 Agriculture sector ............................................................................................................ 36

4.2.3 Self-employment sector ................................................................................................... 38

4.2.4 Other sector ..................................................................................................................... 38

4.2.5 Livestock production ....................................................................................................... 38

4.2.6 Entertainment and electronic equipment possession ........................................................ 39

4.3 Income and expenditure structure ....................................................................................... 39

4.3.1 Income analysis ............................................................................................................... 39

4.3.2 Expenditure analysis ........................................................................................................ 41

4.4 Recorded fish species ......................................................................................................... 41

4.5 Fishing gears ...................................................................................................................... 42

4.6 Firewood consumption ....................................................................................................... 43

4.7 Water sample analysis ........................................................................................................ 44

CHAPTER 5: DISCUSSION .................................................................................................. 66

CHAPTER 6: CONCLUSION AND RECOMMENDATION ................................................ 75

REFERENCES: ....................................................................................................................... 78

Appendix I. Population structure by gender and age of the study area ..................................... 82

Appendix II. Percentage distribution of literacy and educational status in the study area ....... 83

Appendix III. Number of households and population by occupation ....................................... 84

Appendix IV. Number of households and population by occupation ....................................... 85

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Appendix V. Income and expenses in surveyed areas in 2010 ................................................. 86

Appendix VI. Per capita income and average household members by village......................... 91

Appendix VI a. Economy breakdown by village in 2010 Shweletpan ...................................... 92

Appendix VI b. Economy breakdown by village in 2010 Mamonkaing ................................... 93

Appendix VI c. Economy breakdown by village in 2010 Hepa ................................................ 94

Appendix VI d. Economy breakdown by village in 2010 Nyaungbin ...................................... 95

Appendix VI e. Economy breakdown by village in 2010 Lonton ............................................. 96

Appendix VII. Expenses in surveyed area in 2010 ................................................................... 97

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LIST OF TABLES

Table 1. Population distribution and gender in surveyed areas ................................................. 45

Table 2. Population composition in interview areas and of the whole village .......................... 45

Table 3. Interviewed population in % of surveyed areas .......................................................... 45

Table 4. Population distribution and density of surveyed areas ................................................ 46

Table 5. Settlement trend in surveyed areas ............................................................................. 46

Table 6. Age structure of surveyed areas according to the official classification ..................... 47

Table 7. Worker`s participation of surveyed areas ................................................................... 47

Table 8. The population of teachers and pupils in each village of the study area ..................... 48

Table 9. The population of teachers, pupils and students in interview areas ............................ 49

Table 10. Population of literacy and educational status in the study area ................................. 49

Table 11. Different roof-, wall-, floor materials and other homes in the study area ................. 50

Table 12. Percentages of different roof-, wall-, floor material in the study area ....................... 51

Table 13. Lighting .................................................................................................................... 51

Table 14. Relationship between lighting and household which has school children ................. 51

Table 15. Water parameters and concentration of elements in water sample (Lonton village)

March 2011 .............................................................................................................................. 52

Table 16. Water source ............................................................................................................. 52

Table 17. Number of boat, motorized boat, motorcycle, bicycle, car and tel. in study site ....... 53

Table 18. Percentage of households that own boat, motorized boat, motorcycle, bicycle, car,

telephone .................................................................................................................................. 53

Table 20. No. of household classified by fishing occupation in the study site .......................... 53

Table 19. Households classified by occupation ........................................................................ 54

Table 21. Population composition by fishing family of the study site ...................................... 57

Table 22. No. of households, population and percentage of farmer family in interview areas . 57

Table 23. Number of livestock in the study site ....................................................................... 57

Table 24. Percentage of households that own livestock............................................................ 58

Table 25. Number of TV, video, radio, cassette, satellite equipment in families ..................... 58

Table 26. Percentage of households with TV, video, radio, cassette and satellite equipment in

interview areas ......................................................................................................................... 58

Table 27. Income structure of surveyed areas in 2010 by occupation ...................................... 59

Table 28. Income/Expense distribution of surveyed areas in 2010 ........................................... 60

Table 29. Expense structure of surveyed areas in 2010 by occupation ..................................... 61

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Table 30. Recorded fish species ............................................................................................... 62

Table 31. No. of household classified by fishing gear in interview areas ................................. 63

Table 32. Size of one gill net classified by different mesh size ................................................ 63

Table 33. Firewood consumption in the study area .................................................................. 63

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LIST OF FIGURES

Figure 1. Maps showing the study area .................................................................................... 13

Figure 2. Drainage system map of Indawgyi region ................................................................. 14

Figure 3. Map of surveyed areas .............................................................................................. 25

Figure 4. Worker and dependents ratio in interview areas ........................................................ 48

Figure 5. Percentage distributions of literacy and educational status in interview areas ........... 50

Figure 6. Map of Indawgyi lake region .................................................................................... 55

Figure 7. Occupational structures in interview areas ................................................................ 56

Figure 8. Percentage of fishing population in interview areas .................................................. 56

Figure 9. Income structure of surveyed areas in 2010 by occupation ....................................... 59

Figure 10. No. of households/ income-/expense-class .............................................................. 60

Figure 11.Expense structure of surveyed areas in 2010 by occupation ..................................... 61

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LIST OF PLATES

Plate 1. Some resources and nature of the lake ......................................................................... 15

Plate 2. Some challenges for the lake ....................................................................................... 16

Plate 3. House structures .......................................................................................................... 64

Plate 4. Some fishing gears and fish species............................................................................. 65

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LIST OF ABBREVIATIONS

FAO Food and Agriculture Organization

GDP Gross Domestic Product

DOF Department of Fishery

WHO World Health Organization

MOEJ Ministery of Environment Japan

NGO Non-governmental Organization

UNDP United Nations Development Program

EC European Commission

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CHAPTER 1: INTRODUCTION

Regional socio-economic analysis are fundamental to thoroughly understand present

conditions, define chances and risks of future developments and indicate possibilities to

minimize negative impacts on human life quality.

In many developing countries a majority of the people are dependent on water-related

natural resources, such as aquatic resources and floodplains, for their livelihood (FAO,

2010). Moreover, some of those countries' GDP rely on their aquaculture.

Indawgyi lake area is one of the largest inland freshwater reservoirs, not only of Myanmar,

but also for Central South East Asia. The lake has a rich and abundant aquatic macrophyte

flora, vital for maintenance of biodiversity and the ecosystem services, which the local

population depends on for their survival and social welfare.

A total of 64 fish species were recorded in the lake basin, including inflowing streams and

marshy areas. Three of them are endemic. The Lake is also the most important bird area of

Myanmar. 97 species of water birds have been recorded (Davies, Sebastian and Chan,

2004).

The Lake area is homestead for eleven village tracts and thirty-seven villages. Its size is

about 1211.39 km² (Naing Naing Latt, July 2010). 10 villages are located on the fringe of

the lake.

There are 7,131 households with a population of 45,345 (Ministry of Forest Department,

Myanmar, Feb 2011). Fishing is besides agriculture the second economic activity and

income source for these people.

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Since many decades Myanmar`s GDP depends on agro- and aquaculture. In 2009-2010

Inland fresh water fish contributed 3.7% of the country`s total GDP, compared to rice 3.4%

(Frauke Kraas, Vorlesung “Myanmar” SS 2011).

The pressure of population growth [annually 1.75% (Department of population, 2008)],

market demand, globalization trend, and lack of knowledge and infrastructure lead to an

unsustainable use of natural resources.

1.1 The aims of the study

This work shall analyse the present socio- economical and environmental situation of the

Indawgyi area in depth, as it is not only important for the local population, but has

significant impact on the ecosystem services, supplied for the whole central South East

Asia. The aim is to deliver baseline data for measures to minimize negative impacts caused

by the predictable future developments.

1.2 General description of the Indawgyi lake area

1.2.1 Topography and drainage

The Indawgyi lake is located in the northern part of the Myanmar and belongs to the

Mohnyin Township, which is part of the Kachin State (Fig 1). Its geographical position is

between latitude 24° 56' North and longitude 96° 39' east, the lake stretches over 23.8km

from north to south, the maximum width is 10 km, the basin is slightly asymmetrical, the

depth of the lake is between 15.88 to 22.19 m, it covers an area of about 120km² and the

catchment area includes about 850km² (Davies, Sebastian and Chan, 2004)). Indawgyi lake

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is surrounded by mountain ranges, 300 m to 1,300 m in elevation above sea level (Ministry

of Forest Department, Myanmar, 2010).

The lake is fed by many streams, dendritic drainage system can be found (Figure 2) .At the

northeast end of the lake, Indaw stream is the only outflow of the lake. This stream runs

towards northeast and enters the Moegaung stream, which feeds its water into the

Irrawaddy river.

1.2.2 Climate and soil

Indawgyi lake area falls within sub-tropical monsoon climate zones, which divide the year

into three seasons. The wet season stretches between June to October, the cold season from

November to February and the dry season from March to May respectively.

The average year-over temperature is between 17°C to 28°C. It can however stretch from as

low as 4.6°C during December and January and to a peak of up 40°C in April. The area is a

mountainous and densely forested region. Thus, it receives heavy rain. The annual rainfall

is about 1,789 mm with the mean relative humidity of 80% to 90%.

Mist is common in the lake basin during morning in the cold season. Days are usually

sunny during the dry and cold season. These climate data were obtained from the

Meteorology and Hydrology Department, Mohnyin Station, Mandalay, 2010.

Meadow alluvial soil is found around the lake area and on the flat plain. It is mainly

composed of silt and clay with a share of approximately 70% and 20% respectively, the pH

value is around 6 and the ratio of nitrogen and carbon is 7:13. This soil is suitable to

cultivate rice, sugarcane, groundnut, bean and vegetable (Naing Naing Latt, 2010).

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Meadow swampy or grey soil is found particularly in poor drainage areas, especially north

of the lake. This is wet throughout the year. The lower ground layers show blue or grey

colour with tiny spots of red or brown. The soil is sticky with high contents of clay. The pH

value is 6.5, i.e. it is slightly acidic. Red and yellow brown forest soil is dominant in the

mountain ranges (Ministry of Agriculture and Irrigation, 2002).

1.2.3 Vegetation and land cover

The flat plains, surrounding the lake are mostly covered by rice fields. Some areas, which

are the seasonally inundated and waterlogged plains surrounding the lake, are covered by

herbaceous marsh, scrub swamp and swamp forest.

In the open water of the lake, especially at the north end between the Nyaungbin and Indaw

stream outflow and at the southern end around the Nanyinkha stream inflow are extensive

areas of herbaceous march and water hyacinths.

Due to the relatively high transparency of the water (3.5m), extensive beds of submerged

and floating leaved macrophytes can be found in some places (Davies, Sebastian and Chan,

2004).

The mountain ridges are mostly covered with broad leaf forests with many teak

(Tectonagrands) individuals.

1.3 Challenges for Indawgyi lake

1.3.1 Overfishing

Over the past decades and on-going a growing number of fishermen migrate into the lake

area. This immigration is supported by a growing market demand for fish and became one

of the most serious threats for a sustainable ecosystem development, caused by overfishing.

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The indigenous people, Shan, Myanmar, Kachin depend primarily on agriculture and use

traditional, low impact fishing techniques, obviously since 1990 migrants use intensive

fishing practice because fishing is their main source of income (Indo-Myanmar

Conservation, 2009)

Fishing is carried out mainly with small motorized boats using gill nets with a variety of

mesh size. Sometime, improper fishing methods can be found, i.e. electric shock fishing.

Baskets are used to catch smaller fish and prawns in the weed margins.

In 2010 the official registration number is 435 fishermen in the Lake. They work on

average 10 months per year, and set the nets twice per day (Indo- Myanmar Conservation,

2010).

In 2008-2009, the total fish production in Myanmar was around 3,542,290 tons, 26 % of it

contributed from freshwater fish, with a considerable share from Indawgyi Lake (Aung

Htway Oo, 2010).

Domestic consumption is estimated at 43 kg per capita per year (Aung Htay Oo, 2010).

Bearing the annual population growth of Myanmar in mind, the scale of the issue for the

ecosystem balance and its negative impact on socioeconomic situation of the region

becomes obvious.

1.3.2 Land use management

Most of the inhabitants of the Indawgyi lake area are engaged in agriculture. 80% of the

total population makes its living from agriculture (Naing Naing Latt, 2010). Issues are that

due to the small size of farms and lack of effective irrigation systems, most of the farmers

can cultivate crop only during the raining season. Most of the farm land directly adjacent

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to the lake and also other farm land are adequate to grow just paddy, because the soil is

sticky containing large proportion of clay.

This monoculture leaches the soil and causes the use of more and more fertilizer, which

forms another negative impact on the water quality- and in the medium term on the eco-

system service. Due to the limited crop production after harvest most of the farmers work

as fishermen, reinforcing the overfishing issue.

1.3.3 Gold mining

Since 1995 gold mining on a commercial scale has developed in Kachin State (Hla Hla

Than, Dec 2006). In the Indawgyi region gold mines are found along its inflow streams,

near the village of Nyaungbin, Nanttaungse, Nammilaung, and Nampade. Sometime some

illegal gold mines can be found near Mamonkaing and Mainnaung in the conservation area.

Most of the local people who own neither farms nor boats often work as daily labourers at

gold mines during the dry and cold season. However, most of the gold miners are migrants.

Mostly mining is operated by Chinese companies (Irrawaddy news magazine, Oct 2006).

The visible threat of gold mining is the blocking of streams, or diversion by mud produced

from the gold mines. Farmers now face water shortages from the stream diversion, and

paddy fields are drying out. The invisible but most dangerous potential threat however is

mercury contamination.

(i) Method

The widely used methods of the gold mining in Indawgyi region is hydraulic mining. This

method directs a powerful stream of water against the gold bearing gravel or sand. This

operation breaks down the material and washes it away through specially constructed

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sluices in which the gold settles, while the lighter gravel is floated off. After that gold is

extracted from gravel or crushed rock by dissolving it in mercury. The gold is recovered

from the solution and melted into ingots.

(ii) Emission of mercury in the environment

Most of the mercury used by this technique is released into the biosphere. Some of it as

elemental mercury vapour, which circulates in the atmosphere for up to a year. Hence it

will be widely dispersed and transported thousands of kilometres from likely sources of

emission (Pollution Probe, 2003, p. 27). It can be readily removed from the atmosphere by

precipitation and is also dry deposited on the earth's surface. . Even after it deposits,

mercury commonly is emitted back to the atmosphere either as a gas or associated with

particles, to be re-deposited elsewhere.

Another share of mercury pollution from gold mining directly accumulates in water and

soil. It appears as inorganic mercury salt and organic forms (e.g. methyl mercury). Some

microorganisms in the water or soil can change inorganic forms of mercury to organic

forms (methyl mercury) (United States Public Health Service, 1996-2010).

(iii) Mercury in fish

In the aquatic environment, most prevalent is mercury in organic form. Such as methyl

mercury, which accumulates in fish tissue. Inorganic mercury, which is less efficiently

absorbed and more readily eliminated from the body than methyl mercury, does not tend to

bio accumulate. Therefore most fish carry trace amounts of methyl mercury. The level of

mercury found in a fish is related to the level of mercury in its aquatic environment and its

place in the food chain. Mercury tends to accumulate in the food chain. Large predatory

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fish species tend to have higher levels than non-predatory fish or species at lower levels in

the food chain (Pollution Probe, 2003).

(iv) Human exposure pathways and health effects

Humans are most likely to be exposed to methyl mercury through fish consumption.

Exposure may occur through other routes as well (e.g. the ingestion of methyl mercury-

contaminated drinking water, from food sources and from breathing contaminated air)

(United States Public Health Service, 1996-2010).

However, the fish consumption pathway dominates these other pathways. Trace amounts of

methyl mercury are not harmful to humans, but the highest level of methyl mercury, for

example in predator fish can pose great risk to people who eat them regularly as outlined in

the following.

Mercury is a known human toxicant. It is poorly absorbed from the gastrointestinal tract.

Once in the body, mercury concentrates in the nerves, liver, and especially the kidneys.

Mercury is a potent cellular toxin, known to decrease neurotransmitter production. It

disrupts important processes within the nerve cells, and decrease important hormones such

as thyroid and testosterone.

Symptoms of mercury poisoning are muscles cramps or tremors, headache, tachycardia,

intermittent fever, acrodynia, personality change and neurological dysfunction (New

Hampshire Department of Environmental Services, 2003).

(v) Ecological effects of mercury

Adverse effects of mercury on fish, birds and mammals include death, reduced reproductive

success, impaired growth and development and behavioural abnormalities. Sub lethal

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effects of mercury on birds and mammals include liver damage, kidney damage, and

neurobehavioral effects. Exposure to mercury can also cause adverse effects in plant such

as death and sub lethal effects. Sub-lethal effects on aquatic plants can include plant

senescence, growth inhibition and decreased chlorophyll content. Sub lethal effects on

terrestrial plants can include decreased growth, leaf injury, root damage, and inhibited root

growth and function (United States Environmental Protection Agency, Dec, 1997).

1.3.4 Firewood consumption

48.3% of total land area in Myanmar is forested between 1990 and 2010 deforestation rate

was on average 0.95% per year (FAO, 2011). Insufficient electric power supply is one

driving factor. More than 50% of deforestation is caused by wood fuel production for

household cooking, lighting, space heating and for commercial businesses (Zin New Myint,

2005).

The Indawgyi lake area has no public power supply. The lake area is surrounded by

reserved forest with an area of 556 km² (Ministry of Forest Department, Myanmar 2004).

So, most of the people totally depend on either protected or open forest for fire wood.

1.3.5 Waste disposal

Solid Waste disposal is a critical issue to the lake. There is no municipal waste collection.

Most of the people who live in the lake fringe area deposit their household waste at the

bank of the lake. Some people, who come to the lake wishing to take a bath, bring their

household waste and throw into the lake. A few people burn the household waste in their

yard.

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Another reinforcing issue increasing the waste amount is tourism. An ancient pagoda is

located on the lake´s open water at the middle of its western edge. An annual pagoda

festival takes place between the end of February and begin of March for 7 to 10 days.

Everyday about 80,000 pilgrims attend the festival (source: locals report, 2010). Most of

the pilgrims and all shopkeepers camp on the bank of the lake near pagoda. All haul their

waste on the bank of the lake.

During the rainy season, the lake expends and the low- lying areas surrounding the lake

basin are flooded. Thus, all waste is washed into the lake by either run off or flood. The

caused water pollution and as a consequence of this the threat of aquatic community

depends on the content of household waste and dissolved materials. Solid waste mostly

consist plastic litter. There is non- biodegradable and biodegradable plastic litter. In

addition the issue of litter in the lake is reinforced by fishermen, using plastic bottles as

fishing tools to flood their nets.

Normal plastics are bio-degradable, but this process needs hundreds of years to complete,

so normally they are not considered as bio-degradable. Only some very specialized

microorganisms, like some bacteria, fungi can biologically degrade plastics, and this

happens only under strictly controlled conditions, not available in this area.

Plastic litter therefore causes serious problems to animals, which have a tendency of

investigating and even ingesting plastics. Whether this behaviour results from the

resemblance of plastics to prey or is an outcome of curiosity is unclear. But in either way,

plastic litter causes major problems. Aquatic animals might be strangled in plastic bags

often causing painful deaths. Ingestion of plastics in general can also lead to death by

blocking the digestive tracks. Plastic waste also blocks soil enrichment and causes soil

contamination as well.

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1.3.6 Hunting

In the cold season the water bird population around the lake is likely to exceed 20,000 birds

(Davies, Sebastian and Chan, 2004). Poisoning of birds is traditionally a popular hunting

practice in the Indawgyi lake area. Some fishermen use it. According to the park wardens,

they mix pesticide and food, and put the food on the floating plants in the lake. Water birds

ingest it and become paralyzed. They are caught and sold in the market. It is a serious threat

to the bird population diversity and consumer as well.

1.3.7 Institutional management

Since 1999 Indawgyi lake is declared conserved as Indawgyi Wetland Bird Sanctuary. It is

managed by dedicated personnel from the Nature and Wildlife Conservation Division. This

organization has emerged, according to The Wildlife, Wild Plants and Conservation of

Natural Areas Law of 1994. It is under responsibility of the Forest Department. The

Indawgyi region staff accounts 21 people. The wardens claim to be under staffed and the

infrastructure for patrolling to be insufficient as outlined in the following examples.

Small-scale capture fishery is practiced and accepted in the lake area. The permit to fish

needs a license, issued by the Department of Fishery (DOF), Myanmar. All fishing gears

require such a license. Fees are variable according to the production levels and capacities.

License fees for small gears are low.

Officially, it is required for all license holders to report their catches. In practice however,

this is unlikely to happen without control. The entire fishery is terminated in May, June,

July and August thus allowing spawning and recruitment (Aung Htay Oo, 2010). In

12

practice, the fishery in the lake goes on throughout the year. The wardens are unable to

prevent this, due to organizational shortage, and lack of powerful law, they claim.

The Myanmar “Mines laws” of 1994 is vague and incoherent. They consist largely of

general statements lacking the clarity regarding waste disposal.

In relation to pollution, Myanmar has no specific laws to govern air and water pollution.

These issues are loosely covered by the Public Health Law of 1972, empowered by the

Ministry of Health.

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Figure 1. Maps showing the study area

Union of Myanmar

Topographic map of Indawgyi lake area

Kachin State

14

Figure 2. Drainage system map of Indawgyi region

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Plate 1. Some resources and nature of the lake

Water birds- Anastomus oscitans (Asian Openbill)

Fisherman`s houses, study area (Hepa village)

Fresh water supply in Lonton village

Surveyed area in Nyaungbin village

Collecting algae for pig food

Small prawn

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Plate 2. Some challenges for the lake

Some waste disposal on the bank of the lake

Some litters are floating in the lake

Gold mining activity



Firewood (2 bullock carts)

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CHAPTER 2: REVIEW OF LITERATURE

2.1 Socioeconomic aspects

Creston Valley (Canada wildlife management area, n.d.) as described and cited on the

Ramsar website highlighted the importance of this wetland ecosystem and its services. It

can serve as an example how wetland ecosystems provide with trillions of US dollars

revenue every year us on a worldwide scale, - entirely free of charges- making a vital

contribution to human health and well- being.

M.A. Abdrobo and M.A Hassaan (2003) provided conceptual and practical guidelines on

how to conduct reliable assessments of the socioeconomic conditions, comparative analysis

of various study sites and consequently establish a set of general guidelines for sustainable

development in the coastal areas of the Mediterranean.

CJ Meintjes (March 2001) development paper 145 for the Development Bank of Southern

Africa stated guidelines for regional socio-economic analysis, including purposes of

regional socio-economic analysis, methodological frameworks and analytical techniques.

Environ Dynamics (Environmental Management Consultants, 2010) reviewed information

on environmental impact assessment for the Elizabeth Bay optimization study, which was

performed in conjunction with plans to extend the life of Namdeb Diamond mine in

Namibia and targeted to meet the objective of acquiring maximum sustainability and to

continue contributing towards the socio-economic well- being of its workforce and their

families.

18

Peadar Kirby (2006) researched the different methods and parameters, developed to

determine the direct and indirect impacts of Globalization and their dynamics on

individuals and communities well-being. Comparisons of strengths and weaknesses as well

as applicability of the results of his studies will be assessed.

Yin Yin Win (June, 2007) described the socioeconomic status of two villages of Maubin

Township, Ayeyarwaddy Division, Myanmar including reproductive biology of fish species

Mystus pulcher.

Dr. Naing Naing Latt, Daw Kyu Kyu Thin and Dr. Seng Aung (July 2010) presented a

research paper regarding the geographical and socioeconomic condition of the Indawgyi

Lake environ.

The EC- Burma/ Myanmar Strategy Paper (2007- 2013, pp. 9-34) recognized that, after

decades of armed conflicts and relative isolation from and by the international community,

Burma/Myanmar is significantly lagging behind its neighbours on most socio-economic

indicators on poverty, health, and education, with a Human Development Index ranking at

129 out of 177. The EC- Burma/ Strategy paper identified, Burma/ Myanmar has one of the

world`s lowest levels in public sector expenditure (approximately 4% of GDP).

The quality of public health services is very low and the de facto introduction of user fees

has contributed to worsening conditions for many segments of the population who cannot

afford proper health care.

In addition the education system is chronically under- funded and poorly managed. One of

the greatest challenges is the low student retention and completion rates.

19

Only 68% 0f the rural population has access to safe water and 57% to safe sanitation (cited

WHO report 2004).

Images Asia & Pan Kachin Development society (Nov, 2004) `s report “At What Price”

pointed out Gold mining in Kachin State, Myanmar and its economic and social impact in

mining areas as well as unsafe working condition for miners.

Food and Agriculture Organization of the United Nations, (2010), published “Inland

Fisheries Resource Enhancement and Conservation in Asia”. It included review papers of

inland fisheries, resource enhancement and conservation covering practices, methodologies,

operational modalities, impacts, constraints and recommendations for the way forward and

one regional synthesis report generated from a regional expert workshop. Included were

ten countries, namely Bangladesh, China, India, Indonesia, the Republic of Korea,

Myanmar, Nepal, Sri Lanka, Thailand and Vietnam.

The Food and Agriculture Organization of the United Nations, (2003) implemented the

mission for Myanmar aquaculture and inland fisheries. The mission identified that

Myanmar urgently needs technical assistance, sustainable development of coastal and

inland aquaculture and management of aquatic resources. It is also strongly recommended

that Myanmar Department of fisheries increase its formal and informal networking with

other line agencies and organizations within Myanmar and also with similar national

networks in other countries.

20

2.2 Environment aspects

Walter K. Dodds, Wes W. Bouska, (Environmental Science Technology, 2009) studied the

development of total Phosphorous and total Nitrogen concentration of the lakes and rivers

in U.S. eco-regions. They also estimated annual economic losses in recreational water

usage, waterfront property, recovery of threatened and endangered species, drinking water

treatment, and microphyte- removal, resulting from human- induced eutrophication.

Their assumption was that eutrophication from anthropogenic activity are ultimately

derived from fertilizers: Fertilizer use patterns can be used to indicate global trends of

eutrophication. The two other assumptions were, river nutrient concentrations are directly

proportional to lake concentrations, and hyper-eutrophication in the lake can be found

mainly during the summer months.

Hla Hla Than (Dec, 2006), investigated the environmental impact caused by the gold

mining area in the Kachin State by analysing water, soil, plant and fish samples from

some selected regions of the state. She claimed that turbidity and biological oxygen demand

(1.21-2.68 ppm) of the Indawgyi lake water samples increase during the summer. High pH

values (8.8-9.2) develop. The concentration of Hg ranges in the lake from 0.059 to 2.858

ppb. This means that during the summer the Hg concentration of the lake was found two

fold higher than the limit, set by the WHO (1ppb). The nutrient concentration, such as

nitrate- nitrogen and phosphate- phosphorus indicate eutrophic conditions for the lake.

Davies, Sebastian and Chan (2004) published a text book of “A Wetland Inventory for

Myanmar”, which is the systematic documentation of 99 wetland sites of Myanmar. It

21

summarizes the results from conducting surveys between 2000 and 2004, funded by the

Ministry of the Environment, Japan (MOEJ).

Nguyen Hung Manh and Nguyen Phuong Thuy (August 2009, Fauna & Flora International)

reported assessment of the fuel- efficient stove programme in Vietnam. In a particular a

survey on the local people`s usage of fuel wood and the introduction of improved stoves

had been carried out. The evaluation stated that for cooking meals about 25% to 35% of

fuel wood can be saved by using improved stoves instead of the traditional local stoves.

The New Hampshire Department of Environmental Services (2003), the Environmental

Fact Sheet, elucidated the sources of mercury emission, the impacts on health and the

environment from mercury contamination: Strategies for reducing man-made releases of

mercury to the environment were depicted.

The United States Public Health Service (1996-2010) described the nature of mercury, fate

and transport of mercury, as well as exposure pathways and metabolism health effects.

The United States Environmental Protection Agency (Dec, 1997) outlined how to fulfil the

requirements of the Clean Air Act Amendments of 1990. It is an eight volume assessment

of the magnitude of U.S. mercury emissions by sources, the health and environmental

impacts of those emissions, and the availability and cost of control technologies. One of

them (Volume VI) is dealing with an ecological risk assessment for anthropogenic mercury

emissions.

Pollution Probe`s Mercury Primer (June 2003) provided an overview of the presence and

effects of mercury in the environment and its impacts of human health. The primer

identified where mercury is being used and released, the risks associated with exposure to

22

mercury and the ways to help prevent mercury pollution. The primer also described what

governments businesses and individuals are doing to eliminate the use of mercury and

prevent its release to the environment. Finally, the primer highlighted that mercury is a

significant global issue and threat to human and ecosystem health around the world.

Visit to an Ocean Planet Web site described the topic “Plastic in the Ocean” cited Western

Regional Environmental Council (1987). It offered enhancing of awareness regarding the

hazard of plastic litter for wildlife in both the marine and fresh water environments.

23

CHAPTER 3: MATERIALS AND METHODS

3.1 Study area

Five villages, Lonton, Mamonkaing, Shweletpan, Hepa and Nyaungbin, located in the

fringe of the lake were chosen as study area (Fig 3). It has an expanse of about 438.72km².

The villages are located at a distance of approximately 42km, 37 km, 31km, 35km and

69km from Mohnyin city respectively.

3.2 Interview-based survey

The stratified random sampling method was applied to choose respondents. One hundred

households with 536 residents have been surveyed and interviewed.

Recorded for each of the families were: Family size, age status, worker/non-worker,

literacy, occupation, income, expenditure for

each family member;

Further subjects of the questionnaire were: access to electricity, water sources and self-

assessment of the family´s socioeconomic

status.

Firewood consumption was also recorded to identify the human impact on the natural

resources. It provides the expenditure item to

analysis socioeconomic as well.

Interviews were conducted during family visits by personal communication.

Some further questions were answered by observation by the interviewer, (e.g. house type).

Local community leader interviews provided general information about villages.

24

3.3 Recording of fish species and fishing gear

Fish species and daily catches, as well as their fishing gear in use were recorded by

interviewing the fishermen at their fields. Identification of the species was performed

according to the book “Inland fishes of Myanmar” (Chavalit Vidthayanon, Apichart

Termvidchakorn & Myint Pe).

3.4 Recording of environmental data

Water samples were collected from the lake and analysed at Yangon Institute of

Technology and at the Institute of Geography, University of Cologne. Rainfall and

temperature data were obtained from the Meteorology and Hydrology Department,

Mohnyin Station, Mandalay. Data about flora and fauna of the Indawgyi Wildlife Sanctuary

were contributed by the Forest Department Myanmar. Soil sample data and all secondary

data were collected by literature reviews. However the secondary data are less likely to be

available and where few research are able to work.

25

Figure 3. Map of the surveyed areas

(A. Lonton, B. Mamonkaing, C. Shweletpan, D. Hepa, E. Nyaungbin)

A

BC

D

E

26

CHAPTER 4: RESULTS

4.1 Social Factors

4.1.1 Population and settlement trend

Interviews were conducted from 19 households in Shweletpan, 22 households in Hepa, 14

households in Manmon Kaing, 18 households in Lonton and 27 households in Nyaungbin.

The family size data were recorded in five villages with 100 households of the surveyed

area. The recorded results regarding family size were 19 households with 89 individuals in

Shweletpan, 14 households with 72 members in Mamonkaing, 22 residences with 124

household members in Hepa, 27 dwellings with 153 residents in Nyaungbin, 18 households

with 98 members in Lonton, respectively (Table 1).

This amounts to an average of approximately 5.4 members per household. The highest

negative deviation from average is in Shweletpan (4.68 person/family) including one family

with 10 members. Lonton also is home to three families with 10 members, but deviates

only slightly positive from average (5.44members/ family). The highest no of

members/family was recorded for Nyaungbin with 5.66 family members (Table 2).

The total no of interviewees was 536 which represent 100 households in all 5 villages

covered. Those represent 7.8 % of the total population in the study area (Table 3). The

average population density was 391 persons in one square mile (150 persons /km²) of the

settlement areas (Table 4). (notice, the different in population no. shown in table 2 and 4

represent the population of the main village and village tract).

The residents’time of respondents are also recorded. The results were split into six groups,

native, and ≤ 10 years, 11-20 years, 21-30 years, 31-40 years and ≥ 41 years.

27

The result stated that only 31% of respondent are native people. Natives are defined to be

born in the area. 34 % of total respondents migrated into the area during the past 10 years

or less. 20% of total respondents are living in the study area between11 and 20 years.11%

of total respondents moved there 21 to 30 ago. Only one person could be found, who has

lived in the area for 57 years, and one other fell into the category < 41 years i.e. 1% of

respondents (Table 5).

The no of immigrants within 20 years is higher than the no of native inhabitants which

indicates that the population of the region has more than doubled within 20 years (less than

1 generation).

4.1.2 Age groups and gender

The interview data have been assigned to thirteen age groups accordingly. The classes

formed were: 0 to 5 years, 6 to 10 years, 11 to 15years, 16 to 20years, 21 to 25years, 26 to

30years, 31 to 35years, 36 to 40 years, 41 to 45years, 46 to 50 years, 51 to 55 years, 56 to

60 years and above 60 years. The census area was as for all other subjects 5 villages with a

population of 536 people.

According to this classification, in all villages except in Nyaungbin, the largest age group

was recorded for the 0 to 5 years class. For Nyaungbin the age group 6 to 10 years had the

highest headcount with 0 to 5 years in the second rank.

For Shweletpan, Nyaungbin and Lonton the lowest population group count fell in the group

56 to 60. In Hepa and Mamonkaing the lowest count was recorded for the age group 61 and

over. Despite some variations, obviously the largest group for the whole study area was

formed from those between 0-5 years old. The lowest headcount overall fell in the group 56

to 60 (Appendix I).

28

The age groups are officially categorized into three classes introduced by the Myanmar

authorities. These are:

0 to 14 considered as children

15 to 60 considered as working classes

61 and above considered as dependents

Besides more specified classification, another reason to deviate from these official classes

was, that in the surveyed villages (especially in Shweletpan and Nyaungbin) a considerable

number of at young people the age between 9 to 14 years, are actually workers and a few

from the age group above 61 effectively still belonged to the working classes. This finding

indicates that the socioeconomic status of the rural areas is of the low level (Table 6).

The gender count as represented in Table 6 was 246 males and 290 females. Females

dominate males in the population of study area. Although gender ratio was approximately

1:1 in Shweletpan, Mamonkaing and Hepa, the deviation came from Nyaungbin (66 males

and 87 females) and Lonton (41 males and 57 females) (Table 1).

4.1.3 Working classes

The numbers of active- (workers) and dependent- population, counted among the family

members, resulted in a ratio 47.6% worker versus 52.4% dependent or inactive of total

respondents in study area.

Comparing the numbers per Village, for Mamonkaing and Hepa the ratio of workers and

dependents differ from the overall results.

The active population in Mamonkaing was 52.8% against 47.2% dependants.

In Hepa the ratio of active versus dependants was 52.4% against 47.6% (Figure 4, table 7).

29

4.1.4 Education and health

Three primary schools, two affiliated middle schools and one affiliated high school exist in

the study area. One primary school each was established in Shweletpan, Hepa and Lonton.

One affiliated middle school was established in Mamonkaing and one in Nyaungbin. Only

one affiliated high school can be found in Lonton. The number of teachers and school

children of each school are as shown in Table 13. Teacher to pupil ratio is 1:33 in

Shweletpan, 1:45 in Mamonkaing, 1:40 in Hepa, 1:100 in Nyaungbin and 1: 25 in Lonton

respectively (Table 8).

The share of pupils and students of the entire population in the interview areas was also

recorded. The percentage of pupils in all villages is higher than 20% except Hepa with

19.35%. The highest percentage of pupils was recorded for Mamonkaing and Nyaungbin

with over 27%. While Shweletpan and Lonton are somewhere in between with about 24%.

Another finding was that Shweletpan and Mamonkaing have no undergraduate students

(Table 9).

The level of literacy is important to define the socioeconomic structure of the households in

the study area. Most of the elder generation i.e. those who fall into the age groups 51-55,

56-60 and above 61years were recorded as monastery level education, whereas most

members of the working class, of both males and females, fell in the primary and middle

school education level due to struggle for their livelihood (Table 10).

The overall literacy percentage in the interview area was recorded at 81.53%. Only 3.36%

of the population was classified as illiterates. Most of the literates visited primary and

middle level school. Only 5.78% (3.17% incomplete + 2.61%) fall into the high school

level class. University graduates constituted 1.87% and university undergraduates were

30

1.31%. All of the graduate University level group and more than 70% of the undergraduate

university students come from Lonton and Nyaungbin villages. This indicates the

socioeconomic status to be of higher level in Lonton and Nyaungbin compared to the other

three villages (Figure 5, Table 10, and Appendix II).

Regarding health, the total number of inhabitants in the study area was 6,880 as shown in

table 7. The study area has only one clinic with one medical doctor and two nurses in

Lonton.

The published figure of 1 medical doctor per 2,985 inhabitants for total Myanmar (WHO,

2004) is more than two times higher than in the study area. The other villages, except

Shweletpan, have health centers without stationary medical doctors. Generally all villages

except Lonton have one midwife each. The nearest hospital is in Mohnyin with 100 beds.

Malaria is prevalent, especially in the wet season. In the cold months, bronchitis and

pneumonia are very common.

4.1.5 House structures

Two types of homes can be found in the interview area. One is normal homes (houses) on

the land and the second type is floating homes, imbedded in boats on the lake.

The structure of normal houses varies between villages, in terms of the roof material and

shape, the construction of the walls and the floors.

The predominant roof structure used in the interview area was thatch, although tin (metal

sheet) was used more frequently in Lonton.

The predominant wall material was bamboo mats or meshwork in all villages included in

the survey. Lonton and Nyaungbin have 2 houses each with brick made walls.

31

The predominant floor material was bamboo in the whole interview area, although timber

structures were found to be used more often in Lonton and Nyaungbin (Tables 11, 12).

14% of all interviewed households were located in boats on the lake, many of them with

Nyaungbin and Shweletpan (Tables 11, 12) as home location.

Plate 3 shows examples of house structures, using different materials. Those were probably

chosen, dependent on the availability and cost. People living in boat homes often are

migrants immigrated for fishing. They often prefer to live in more temporary structures.

4.1.6 Electric power supply

Access to electric power is unequal between the different villages in the study area.

Nyaungbin has no public electricity at all. Lonton has a public generator installed by the

government in 1996. It supplies electricity for governmental offices and street lighting from

6:00 pm to 9:00.

Other than that, three sources for electricity supply are available, but not area-wide

accessible.

The first one is private and private public supply, i.e. some residents use their

generator for their own need plus supply their neighbourhood.

The second one is supply by monastery.

The third one is supply by local community.

All supply sources charge similar rates. The charge amount depends on the appliances the

power is used for. - E.g. one electric lamp costs 3000 Kyats (appr. € 3.00) per month and

usage from 6:00 to 9:00pm.

Electricity supply data were recorded in the five villages with 100 households of the

surveyed areas. The outcome of these 100 respondents was that 5 households in Shweletpan

32

(26.3% of respondents), 13 households in Hepa (59% of respondents), 10 households in

Mamonkaing (71% of respondents, 14 households in Lonton (78% of respondents) and 20

households in Nyaungbin (74% of respondents) have access to electric power supply. The

database may be too small to claim statistical exactness. While Lonton, Nyaungbin and

Mamonkaing seem to be close in development, the Shweletpan result shows clearly the

lowest access rate, while Hepa is somewhere in between. The average access rate of the

study area is approximately 62% of total households which have access to electric power

supply (Table 13).

According to observations, a correlation between those families with access to electric

power supply and households which have school children could be detected. 55% of the

total respondents, who have school children, have access to electricity. 7% of interviewees,

who have no school children, have access to electricity (Table 14).

4.1.7 Water supply

The inhabitants of the study site have access to two types of water sources:

1. surface water (lake)

2. ground water (tube wells)

The pH value of lake is about 7.8 and the value of tube well is between 7.5 and 7.6. So,

both are chemically almost neutral and as such usable for drinking and household. The

result of lake water analysis, as described in Table 15, indicates the water is usable for

drinking. Lake water is by far the most used water source in the study area as the recordings

show.

The depth of the aquifer, important for tube well building, is between 60 and 70 feet in the

study area.

33

The following data of water sources for drinking and household use were recorded during

the interviews. Another finding of these interviews was that none of the respondents uses

separate sources for drinking and household water.

15.8 % of the respondents in Shweletpan obtain their water from tube wells and 84.2 % rely

on lake water for both, drinking and household use. In Hepa 18.2 % use tube wells as

source for drinking and cooking water and 81.8 % draw it from the lake for both purposes,

14.3% of the respondents in Mamonkaing use tube well water and 85.7 % are lake water

users. In Lonton just 11.1% use tube well water supply and 88.9% depend on lake water. In

Nyaungbin 25.9% use tube wells as water source and 74.1 contribute to the lake water user

community (Table 16).

In total 82% of all respondents depend on lake water for drinking and household whilst just

18% are tube well users (Table 16).

4.1.8 Transportation and communication

The Indawgyi Wildlife Sanctuary is connected to Hopin and Mohnyin by a motor road

(Figure 6).

Two lane dirt roads surround the lake almost entirely. One of them connects Hopin, with

the villages Nammon, Hepa, Hepu and Losant. The west circular road separates from the

Hopin- Losant road close to the village of Nammon and connects Lonton and Nyaungbin

before it leaves the Sanctuary to the north. Dead end and side roads connect the various

settlements on the west side of the lake, which are located off the “main road”.

During the wet season, these unfortified roads are in real bad condition and often blocked

by landslides. To facilitate the transportation of vital goods, roads often are repaired on a

self-help basis by the local authority.

34

The inter-village connection roads are mostly used by private people for goods interchange

and sale of own agriculture products, fish and other goods, using cars, small lorries/

tractors, motorcycles, bicycles. During the dry and cold seasons there is a kind of public

transportation. It is a once- per- day connection, operated by privately owned cars. Every

morning at a fixed schedule a car is collecting passengers and transports them to their

destinations against fixed fees. This service is accessible for everyone who pays the

charges.

The second equally important transportation way besides the sometimes impassable roads

is by boat or motor boat. The number of boats and percentage of households who own one

or more boats, motorized or without motorized were recorded in the five villages with 100

respondents of the survey area. At the same time the data for motorcycles, bicycles and

cars were recorded.

The finding was the possession of motorized boats is dominant over other all transportation

items in every village.

The highest dispersal rate of bicycles is in Shweletpan. None of the inhabitants however

owns a motorcycle or other motorized land transportation vehicle. The possession of cars in

the study area is almost zero. An exception is Nyaungbin, where 2 cars could be recorded

(Table 17 and 18).

Regarding communication there is only one public telegraph office in the entire study area.

It is located in Lonton.

In Hepa, Lonton and Nyaungbin some private telephones have been recorded (Table 17 and

18). These are CDMA mobiles and established in 2008. Most of the local people depend on

the use of these private telephones. Usually the owners collect charges for use.

35

4.2 Economic Factors

The economic activities of the study area are divided into four sectors.

(1) Fishery sector

(2) Agriculture sector

(3) Self -employment sector

(4) Other sectors

Workers of respective sectors in addition to their main tasks often take up casual jobs and

small scale animal husbandry, cultivation of crops or open retail shops. Occupational

structure and respective percentage are shown in figure 7, table 19 and appendix III.

4.2.1 Fishery sector

This is the major branch of economic activity within the study area. The fish fauna in the

lake is manifold. The inhabitants of the area catch fish in the lake, employing various

fishing implements. Some of them catch fish in the Indawgyi lake contribution or outflow

streams as well. Almost half of all fishermen were found to be involved not only in fishing

but also undertake side-jobs in crop cultivation, especially paddy cultivation in rainy

season (i.e. fishermen & farmer, it is explained more detail in agriculture sector), as casual

workers, hired especially in seasonal agricultural activities either as monthly or daily

employees, or work in open retail.

According to their job category fishing families were subdivided into four categories (Table

20).

(1) Fishermen

(2) Fishermen & farmer

(3) Fishermen & general worker

36

(4) Fishermen and retailer

Eighty- four households, comprising of 205 members, were recorded as fishing families –

(fishing includes all 4 categories above) in the interview areas.

This category includes 37 members in Shweletpan, 38 members in Mamonkaing, 59

members in Hepa, 42 members in Nyaungbin and 29 members in Lonton. They altogether

constitute 38.25% of the total population in interview areas and represent 84% of total

respondents.

The percentages by village are shown in figure 8, table 21.

The largest fishing population percentage was found in Mamonkaing, the second largest in

Hepa. Nyaungbin had the lowest fishermen percentage related to the population number.

Shweletpan and Lonton were somewhere in between (Table 21).

An interesting finding was, that some tribes resist to work as fishermen. This reason is

caused by a religious taboo. It is also forbidden to catch fish within one mile radius of the

pagoda in the lake. Another reason for no fishing is that there are 6 fishery ban zones with

an area of 0.5 sq. mile each. They have been established by the Indo Myanmar

Conservation (NGO, 2010).

4.2.2 Agriculture sector

Agriculture is the second important income generating activity in the interview areas.

5.78% of the total population in the interview areas engaged in agriculture (Table 22).

Paddy is the main cultivated crop. Most of the agriculture lands are found on the lake

fringe. Types of cultivated land are generally divided into four main classes.

(1) Le lands, which are mostly found in Indawgyi plain, are broken up into many small

units. Farmers cultivate paddy, and the amount of harvest depends on the rainfall.

37

(2) Ya lands, which are found along the streams and on the forest land, where corn, maize,

groundnut, sesame and mustard are grown.

(3) Garden lands, which include fruit gardens, home gardens and vegetable gardens, where

mangoes, citrus fruits, flowers and vegetables are grown.

(4) Taung ya lands, which are found on the mountain slopes. Taung ya land usually has

only a thin cover of soil. It is invested in deforested areas and taung-ya paddy, maize,

sesame, pulse and vegetable are grown.

Agriculture practice is of intensive and monoculture character. Generally the rainfall is

regular and abundant, sometimes precipitation is insufficient to plough and the rain comes

too late for planting. There is no dam or canal system to irrigate the farms. So farmers

totally depend on rainfall for cultivation. Most of the farmers in the interview areas own 5

to 6 acres of farm land. Some of the land owners have no sufficient manpower resources for

farming. They hire labourers during the farming seasons. The agriculture labourers are

compensated by 100 baskets of paddy in average, which equals approximately €200 income

during the entire season. These incomes however vary, dependent on the working duration,

determined by the farm size and type. Transplantation and harvesting are done mostly by

women. The charges are in the order of € 20 per acre each. Most of the farmers in the

interview areas have one team of cattle or buffaloes. One family each in Lonton and Hepa

owns a tractor.

All farmers in the interview areas earn their extra income by undertaking side jobs. Fish

capture in paddy fields or in streams was found to be one of the most common side- jobs.

The caught fish were not only a source for family food but also for market. Some farmers

undertake casual jobs by renting their bullock cart for firewood transportation and so on.

Some operate a retail shop or a mini store (Table 22).

38

4.2.3 Self-employment sector

Self- employment sector was the third largest sector in the interview areas. Five

households, comprising 17 members, were recorded for this sector. It represents 3.17% of

the total population. This sector included gold miners, ice machine owners, car rental, rice

mill owners, mechanics, tailors and tea shopkeepers (Table 19 and appendix IV).

4.2.4 Other sector

This sector consists of only one family with 2 members comprising 0.37% of total

population in interview areas. Government staffs were recorded in this sector (Table 19 and

appendix IV).

4.2.5 Livestock production

Livestock production is not really existent in the interview areas. It is mostly practiced as

means of subsistence for the families. However cattle and buffalos are important for

agriculture. Chicken and pigs are raised for food. 76 cows, 23 buffaloes, 42 pigs and 256

chickens in the interview areas were recorded (see table 23).

The records prove that while 22.2% of the households in Lonton own one or more cows,

only about 7.1% of the families in Mamonkaing and Nyaungbin are cow owners.

18. 2% of the households in Hepa and 15.8% of the households in Shweletpan own cows.

None of the families in these two villages possesses buffalos. 11.1% of household in

Lonton own one or more buffalos. About 7.1% of the households in Nyaungbin and

Mamonkaing hold buffalos.

39

The highest share of households which own pigs and chicken was found in Shweletpan, the

lowest in Nyaungbin. The other 3 villages, Hepa, Mamonkaing and Lonton were

somewhere in between. All three have the same percentage of pig and chicken ownership

(Table 24).

4.2.6 Entertainment and electronic equipment possession

With intent to obtain a measure for economic wealth of the various households in the

interview areas, the ownership of television sets, video recorders, radio receivers, cassette

recorders and satellite receiving equipment were recorded ( Table 25).

Lonton families possessed more TV sets and video items than those in the other villages.

Shweletpan families owned more radio and cassette items than the families in other

villages. Only one family in Hepa owned satellite receiving equipment (Table 26).

4.3 Income and expenditure structure

4.3.1 Income analysis

General:

Incomes of households in the surveyed areas vary from < kyat 850,000 (appr.US$ 830 to as

high as > kyat 7.3 Mio. (appr. US$ 10,300) as recorded in Appendix V, household number

89 and 98.

In general for the interviewees no correlation between occupation and income was found.

For example the highest income (>7.3 Mio kyat) was achieved by a self -employee

(Appendix V, ID no 98) another self employee had an income of < 1.4 Mio kyat (ID no.

96). Similar discrepancies were detected for all other occupation groups. One fish general

40

worker´s income was as low as 900,000 Kyat (ID no. 74) and at the high end a fish-general

worker was able to achieve an annual income of 2.500.000 Kyat (ID no. 50).

The number of household members was counted between 2 (ID nos. 12 & 70) and 10 (ID

no. 60, 61, 72, 90). The higher the number of household members, the higher is the

likelihood that these household family members live below the World Bank defined

poverty index line (US$ 1.25 per person per day). The detailed results are part of appendix

V.

To develop income and expense structures by occupation and by village, 6 income classes

have been formed. Those are:

1. ≤ 0.9 Mio. kyat, 2. ˃ 0.9 - 1.2 Mio. kyat, 3. ˃ 1.2 - 1.5 Mio. kyat

4. ˃ 1.5 - 2 Mio. kyat, 5. ˃ 2 - 3 Mio. kyat und 6. ˃ 3 Mio. kyat.

Income by occupation: The classes 4 (37 interviewees) and 3 (24 interviewees) have the

highest no of members. Fishermen form the largest occupation group in both classes. They

are also majority in classes 2 and 5. None of them exceeded the 3 Mio Kyat income level.

One fish farmer, two farmer with shop and 2 self employees form this highest income

group. The affiliation of the different occupations to the 6 income classes is listed in Table

27 and Figure 9.

Income class affiliation of households: As households and occupations are closely linked

the data look similar Table 28 and Figure 10 contain the data of household affiliation to the

income classes.

The classes by village and the average income per household member as well as

information about the sample sizes are documented in Appendices VI - (a), (b), (c), (d) and

41

(e). As the number of Interviewees and the household member numbers are different

between the villages, for comparison it is recommendable to use the per capita annual

income. The results are summarized in Appendix VI.

4.3.2 Expenditure analysis

General:

The structure of the analysis done is identical to the income breakdown. Therefore no

detailed description is made here.

As measure for the ratio between income and expense a column called “surplus” was

introduced in Appendix V. It shows that 1 Hepa- , 5 Nyaungbin- and 2 Mamonkaing -

households spent more than their respective incomes. Two of them belonged to the “below

poverty index” households.

Expense by occupation data are outlined in Appendix VII Table 29 and Figure 11.

Expense class affiliation of households is documented in the same Table 28 and Figure 10

as the income data.

An expense breakdown by household members was not judged important and therefore not

part of this study, as it adds only little meaningful information.

4.4 Recorded fish species

The recorded fish species found in the lake and the associated streams (in and outflow) are

listed in Table 30. Among the species recorded Notopterus notopterus and Puntius chola

predominate in the catch according to the records during February, which is part of the dry

season. These species could be caught everywhere in lake and streams (Plate 4).

42

4.5 Fishing gears

The kinds of fishing gear in use are an indicator for the achievable income of the fisher

households and disclose risks of overfishing and fish species extermination.

To analyse the situation in the surveyed areas under these aspects, fishing gear utilized

were recorded. Fish- and gill-nets used, are categorized in four classes, 0.75"-1.0"meshsize,

1.75"-2.0"meshsize, 3.25"-4.0"- 4.5" mesh size and 7.25"meshsize. In addition freshwater

prawn traps were recorded (Table 31, and plate 5).

14.3% of total fishing families in the interview area (84 households) used small mesh size

gill nets (0.75"-1.0"meshsize).

21.4% of total fishing families used large mesh size gill nets (7.25").

30.9% used medium-small size nets (1.75"-2" mesh size)

65.5% of total fishing households used medium-large mesh size gill nets (3.25"- 4"- 4.5")

7.1% of the fishermen household used prawn traps (Table 31).

Obviously, different species of fish are caught, using different mesh size nets. Most fisher

households use multiple nets, dependent on the fish category they are trying to catch.

Season and proliferation widely determine which nets are used.

The different fish species have different market prices and therefore gain different incomes.

The prices for small fish are generally lower than those for larger species. However the

prices of the different gill nets are almost the same and rank around 10,000 Kyats/net (= €

10.00).

Most of the fishermen however had to pay 20% surplus, because they could not pay cash

down. The life time of the gill nets is 1 to 3 years. Due to shortage in income most of the

fishermen repair their nets and use them up to 7 years.

43

Length and depth of nets vary dependent on their mesh size (Table 32). In daily practice 10

to 17 nets are knotted together to improve the catch result.

4.6 Firewood consumption

Wood fuel is by far the most used energy source for cooking and heating all over the

Indawgyi area.

25% of all households interviewed, collected the wood themselves. 75% bought their

firewood requirements from different suppliers. These suppliers cut wood from near

forests, either legally or illegally. The market prices vary from 15,000 Kyat to 20,000 Kyats

per 2 bullock carts (= 0.7 ton) and depend on the associated transportation costs.

The consumption of each household per year was recorded in surveyed areas. The average

total consumption of 100 household with 536 members was 169.44 tons per year. The

average consumption rate per person calculates to 0.32 ton per year. However in

Shweletpan, Mamonkaing and Lonton the per capita consumption was recorded to be

approximately 10% below average (0.29 ton / person/ year). Nyaungbin inhabitants had a

10% higher firewood demand than the average. They consume 0.35 tons per person per

year in average. One reason for this increased demand may be a tea shop and the small

restaurant, both residing in Nyaungbin. They consume more fuel wood for their business

compared to others (Table 33).

They all use the traditional three legged stove and cook in open air during the cold and dry

season. It prevents indoor air pollution but is not efficient for wood consumption.

44

4.7 Water sample analysis

Considering that the Indawgyi lake is the major drinking water source for the inhabitants of

the area (82% of total household water originates from the lake), lake water quality is of

fundamental importance for the health and welfare of the population. Therefore water

samples of the lake have been taken and analysed.

The samples were extracted close to Lonton. Part of the analysis had been conducted at

the Yangon Institute of Technology, others like nitrite, nitrate, mercury, sulphate and

phosphorus have been accomplished by the Institute of Geography, University of Cologne.

The results are listed in table 15.

Fortunately no nitrite, no nitrate, no phosphate, no sulphate and no mercury traces could be

detected in the water samples. According to the World Health Organization (WHO) the

range for the medium alkalinity is 50 – 250 mg/l the analysis proofed that the Indawgyi

lake water (tasted at 98mg/l) does not exceed this value.

The concentration of chlorides was determined to be in the range 1.58 mg/l, an indication

that the water was polluted, neither from sewage nor from weathering of some sedimentary

rocks.

45

Table 1. Population distribution and gender in surveyed areas

No Village Household Male Female Total

Population Percent

1 Shweletpan 19 42 47 89 16.61

2 Mamonkaing 14 34 38 72 13.43

3 Hepa 22 63 61 124 23.13

4 Nyaungbin 27 66 87 153 28.55

5 Lonton 18 41 57 98 18.28

Total 100 246 290 536 100

Table 2. Population composition in interview areas and of the whole village

No Village interviewed total/Village

Households Population Households Population

1 Shweletpan 19 89 97 337

2 Mamonkaing 14 72 280 1878

3 Hepa 22 124 172 1015

4 Nyaungbin 27 153 428 2216

5 Lonton 18 98 229 1434

Total 100 536 1206 6880

Table 3. Interviewed population in % of surveyed areas

No Village Household Male Female interviewed

Population % of total popul.

1 Shweletpan 19 42 47 89 26,41

2 Mamonkaing 14 34 38 72 3,83

3 Hepa 22 63 61 124 12,22

4 Nyaungbin 27 66 87 153 6,90

5 Lonton 18 41 57 98 6,83

Total 100 246 290 536 7.8

46

Table 4. Population distribution and density of surveyed areas

ID Village Tracts Population Area (sq. ml) Density/sq. ml

1 Shweletpan 10,441 9.6 1087

2 Mamonkaing 2,999 12.16 246

3 Hepa 3,399 9.6 354

4 Nyaungbin 3,049 6.4 476

5 Lonton 3,681 22.4 164

Total 23,569 60.16 391

Table 5. Settlement trend in surveyed areas

living years

Shw

elet

pan

Mam

onkai

ng

Hep

a

Nyau

ngbin

Lonto

n

Total

HH %

native 3 5 7 5 11 31 31

≤ 10 year 6 2 9 13 4 34 34

11-20 5 4 2 7 2 20 20

21-30 5 1 3 1 1 11 11

31- 40 0 1 1 1 0 3 3

≥ 41 0 1 0 0 0 1 1

Total 19 14 22 27 18 100 100

47

Table 6. Age structure of surveyed areas according to the official

classification

Age

0-14 15-60 ≥ 60

Shweletpan

Total 41 47 1

Male 16 26 0

Female 25 21 1

Mamonkaing

Total 28 43 1

Male 13 21 0

Female 15 22 1

Hepa

Total 46 76 2

Male 25 38 0

Female 21 38 2

Nyaungbin

Total 62 85 6

Male 25 38 3

Female 37 47 3

Lonton

Total 39 56 3

Male 13 27 1

Female 26 29 2

Total of study area

Total 216 307 13

Male 92 150 4

Female 124 157 9

Table 7. Worker`s participation of surveyed areas

No Village Active Dependency

Population % Population %

1 Shweletpan 42 47.19 47 52.81

2 Mamonkaing 38 52.78 34 47.22

3 Hepa 65 52.42 59 47.58

4 Nyaungbin 66 43.14 87 56.86

5 Lonton 44 44.90 54 55.10

Total 255 47.57 281 52.43

48

Figure 4. Worker and dependents ratio in interview areas

Table 8. The population of teachers and pupils in each village of the study area

No Village Number of Number of

Teachers Scholars

1 Shweletpan

3 98 (primary school)

2 Mamonkaing

9 403 (primary attach-middle)

3 Hepa

3 120 (primary school)

4 Nyaungbin

10 1000 (primary attach-middle)

5 Lonton

20 500

(primary and one attach-high

school)

0%

10%

20%

30%

40%

50%

60%

Workers

Dependents

49

Table 9. The population of teachers, pupils and students in interview areas

No Village Number of scholars Total %

University

students Total %

Teacher Male Female Male female

1 Shweletpan

3 8 1 21 23.56 0 0 0 0 (primary school)

2 Mamonkaing

9 9 11 20 27.78 0 0 0 0 (primary, attach-

middle)

3 Hepa

3 10 14 24 19.35 0 2 2 1.61 (primary school)

4 Nyaungbin

10 14 28 42 27.45 2 1 3 1.96 (primary, attach-

middle)

5 Lonton

20 9 15 24 24.49 1 1 2 2.04 (primary, attach-high

school)

Table 10. Population of literacy and educational status in study area

No Education Level Shweletpan Mamonkaing Hepa Nyaungbin Lonton Total

1 Monastery 3 9 3 15 4 34

2 Primary (Attending) 16 12 14 31 15 88

3 Primary (Incomplete) 28 14 33 29 20 124

4 Middle (Attending) 4 3 9 9 4 29

5 Middle (Incomplete) 15 12 32 36 19 114

6 High (Attending) 1 5 1 2 5 14

7 High ( Incomplete) 2 5 0 6 4 17

8 Undergraduate university 0 0 2 3 2 7

9 Graduate university 0 0 2 3 5 10

Total Literate 69 60 96 134 78 437

10 Illiterate 1 1 10 4 2 18

11 Young children 19 11 18 15 18 81

Total 89 72 124 153 98 536

50

Figure 5. Percentage distributions of literacy and educational status in interview areas

Table 11. Different roof-, wall-, floor materials and other homes in the study area

No. Village

Roof Wall Floor other

thatch yon tin

bamboo brick wood bamboo wood on

the

boat

metal

sheet

1 Shweletpan 14 0 0 14 0 0 12 2 5

2 Hepa 19 1 1 19 0 2 14 7 1

3 Mamonkaing 6 4 2 8 0 4 5 7 2

4 Lonton 4 2 12 11 2 5 4 14 0

5 Nyaungbin 8 8 5 18 2 1 10 11 6

Total 51 15 20 70 4 12 45 41 14

Monastery

6%

Primary

(Attending)

17%

Primary

(Incomplete)

23%

Middle (Attending)

6%

Middle

(Incomplete)

21%

High (

Attending)

3%

High (

Incomplete)

3%

Under graduate

1%

Graduate

2% Illiterate

3%

Young children

15%

51

Table 12. Percentages of different roof-, wall-, floor material in the study area

*Yon is palm leaves.

Table 13. Lighting

ID Village HS

lighting no lighting Total lighting %

1 Shweletpan 5 14 19 26.3

2 Hepa 13 9 22 59

3 Mamonkaing 10 4 14 71

4 Lonton 14 4 18 78

5 Nyaungbin 20 7 27 74

Total 62 38 100 62

Table 14. Relationship between lighting and household which has school children

Category Households in Study site %

Schooling + Lighting 55 55

schooling + non lighting 14 14

non schooling + lighting 7 7

non schooling + non lighting 24 24

Total 100 100

No Village

Roof Wall Floor other

%

thatch

%

yon*

% tin %

bamboo

%

brick

%

wood

%

bamboo

%

wood

% on

the boat metal

sheet

1 Shweletpan 73.68 0 0 73.68 0 0 61.16 10.53 26.32

2 Hepa 86.36 4.55 4.55 86.36 0 9.09 63.64 31.82 4.55

3 Mamonkaing 42.86 28.57 14.29 57.14 0 28.57 35.71 50.00 14.29

4 Lonton 22.22 11.11 66.67 61.11 11.11 27.78 22.22 77.78 0

5 Nyaungbin 29.63 29.63 18.52 66.67 7.41 3.70 37.03 40.74 22.22

Total 51.00 15.00 20.00 70.00 4.00 12.00 45.00 41.00 14.00

52

Table 15. Water parameters and concentration of elements in water

sample (Lonton village) March 2011

Parameter Result

WHO & EU

guideline

pH 7.8 6.2-8.4

Conductivity (μS/cm) 142 250 μS/cm

Iron (mg/l) 0.23 0.2mg/l

Total hardness (mg/l) 69 500mg/l

Total alkalinity (mg/l) 98 <50 - ˃250 mg/l

Dissolved oxygen (mg/l) 5.6 no guideline

Biological oxygen demands (BOD) (mg/l) 0.8 no guideline

Chloride (mg/l) 1.58 250mg/l

Fluoride (mg/l) 0.09 1.5mg/l

Nitrite (mg/l) 0.00 0.50mg/l

Nitrate (mg/l) 0.00 50mg/l

Phosphate (mg/l) 0.00 no guideline

Sulphate (mg/l) 0.00

500(WHO)

250 (EU)mg/l

Mercury (mg/l) 0.00 0.001mg/l

Table 16. Water source

No. Village

HS

drinking water

Household

water

Total

drinking water Household

water

tube

well Lake

tube

well Lake

tube

well

%

Lake

%

tube

well

%

Lake

%

1 Shweletpan 3 16 3 16 19 15,79 84,21 15,79 84,21

2 Hepa 4 18 4 18 22 18,18 81,82 18,18 81,82

3 Mamonkaing 2 12 2 12 14 14,29 85,71 14,29 85,71

4 Lonton 2 16 2 16 18 11,11 88,89 11,11 88,89

5 Nyaungbin 7 20 7 20 27 25,93 74,07 25,93 74,07

Total 18 82 18 82 100 18 82 18 82

53

Table 17. Number of boat, motorized boat, motorcycle, bicycle, car and tel. in the

study site

No Village Boat Motorized boat Motorcycle Bicycle Car Tel

1 Shweletpan 5 12 0 19 0 0

2 Hepa 12 16 2 7 0 2

3 Mamonkaing 2 12 4 2 0 0

4 Lonton 3 12 5 8 0 2

5 Nyaungbin 5 21 5 5 2 1

Total 27 73 16 41 2 5

Table 18. Percentage of households that own boat, motorized boat, motorcycle,

bicycle, car, telephone

No Village Boat Motorized boat Motorcycle Bicycle Car Tel

1 Shweletpan 26.32 57.89 0 73.68 0 0

2 Hepa 27.27 63.64 9.09 27.27 0 4.55

3 Mamonkaing 14.29 78.57 28.57 7.14 0 0

4 Lonton 16.67 66.67 27.78 44.44 0 11.11

5 Nyaungbin 18.52 74.07 14.81 18.52 3.70 3.70

Table 20. No. of household classified by fishing occupation in the

study site

Occupation Category

Shw

elet

pan

Mam

onkai

ng

Hep

a

Nyau

ngbin

Lonto

n Total

Household %

Fishermen 10 4 5 17 8 44 44.00

Fishermen & farmer 2 1 2 0 1 6 6.00

Fishermen & general worker 6 7 9 2 2 26 26.00

Fishermen & retailer 0 2 4 1 1 8 8.00

Total 18 14 20 20 12 84 84.00

54

Table 19. Households classified by occupation

Occupation

Shw

elet

pan

Mam

onkai

ng

Hep

a

Nyau

ngbin

Lonto

n

Tota

l

I. Fishermen

(1) Fishery only 10 4 5 17 8 44

(2) Fishery + agriculture labour 4 5 3 2 14

(3) Fishery + general worker 2 1 4 2 0 9

(4) Fishery+ retail shop 0 2 4 1 0 7

(5) Fishery + gold panning 0 1 2 0 0 3

(6) Fishery + farmer 2 1 2 0 1 6

(7) Fishery + self employment 0 0 0 0 1 1

subtotal 18 14 20 20 12 84

II. Farmer

(1) Agriculture only

(2)Agriculture+ shop 0 0 1 2 2 5

(3) Agriculture + selling fruit+ teacher 0 0 0 0 1 1

(4) Agriculture+ gold planning 0 0 1 0 1 2

(5) Agriculture + general worker 1 0 0 0 1 2

III Self employment

(1) Gold panning 0 0 0 1 0 1

(2) ice machine+ car rental 0 0 0 1 0 1

(3) rice mill 0 0 0 1 0 1

(4) Tailor + technical 0 0 0 1 0 1

(5) Tea shop 0 0 0 1 0 1

IV. Others

(1) Government staff 0 0 0 0 1 1

100

55

Figure 6. Map of Indawgyi lake region

56

Figure 7. Occupational structures in interview areas

Figure 8. Percentage of fishing population in interview areas

Fishermen

37%

Fishermen &

farmer

7%

Fishermen &

general worker

27%

Fishermen & shop

9%

Farmer & shop

7%

Farmer &

general worker

5%

Self employment

7% Others

1%

0,0%

10,0%

20,0%

30,0%

40,0%

50,0%

60,0%

Shweletpan Mamonkaing Hepa Nyaungbin Lonton

57

Table 21. Population composition by fishing family of the study site

Village Households Population Total

Male Female Population %

Shweletpan 18 20 17 37 41.57

Mamonkaing 14 19 19 38 52.78

Hepa 20 33 26 59 47.58

Nyaungbin 20 25 17 42 27.45

Lonton 12 15 14 29 29.59

Total 84 112 93 205 38.25

Table 22. No. of households, population and percentage of farmer family in interview

areas

Occupation

Category

Shw

elet

pan

Mam

onkai

ng

Hep

a

Nyau

ngbin

Lonto

n

Total

HH Pop HH Pop HH Pop HH Pop HH Pop HH Pop %

Farmer &

shop 0 0 0 0 1 3 2 7 3 8 6 18 3.36

Farmer &

general

worker 1 5 0 0 1 3 0 0 2 5 4 13 2.43

Total 1 5 0 0 2 6 2 7 5 13 10 31 5.78

Table 23. Number of livestock in the study site

No Village Cow Buffalo pig chicken

1 Shweletpan 7 0 19 131

2 Hepa 20 0 9 76

3 Mamonkaing 13 3 5 12

4 Lonton 16 8 7 34

5 Nyaungbin 20 12 2 3

Total 76 23 42 256

58

Table 24. Percentage of households that own livestock

No Village Cow (%) Buffalo (%) pig (%) chicken (%)

1 Shweletpan 15.79 0 36.84 47.37

2 Hepa 18.18 0 18.18 18.18

3 Mamonkaing 7.14 7.14 14.29 14.29

4 Lonton 22.22 11.11 11.11 11.11

5 Nyaungbin 7.41 7.41 7.41 3.70

Table 25. Number of TV, video, radio, cassette, satellite equipment in

families

No Village TV Video Radio Cassette Satellite

1 Shweletpan 1 1 4 6 0

2 Hepa 2 2 4 5 1

3 Mamonkaing 0 0 1 1 0

4 Lonton 5 5 2 3 0

5 Nyaungbin 7 7 4 5 0

Total 15 15 15 20 1

Table 26. Percentage of households with TV, video, radio, cassette and satellite

equipment in interview areas

No Village

TV

(%) Video (%) Radio (%) Cassette (%) Satellite (%)

1 Shweletpan 5.26 5.26 21.05 26.32 0

2 Hepa 9.09 9.09 18.18 22.72 4.55

3 Mamonkaing 0 0 7.14 7.14 0

4 Lonton 27.78 27.78 11.11 16.67 0

5 Nyaungbin 25.93 25.93 7.41 11.11 0

59

Table 27. Income structure of surveyed area in 2010 by occupation

Income by Occupation Fishermen

Fish

farmer

Fish general Fishermen Farmer Farmer general Self others

Total

(Mio Kyat) worker & shop & shop Worker employment HH %

≤ 0,9 0 0 1 0 0 1 0 0 2 2

>0,9 - 1,2 8 3 3 1 0 0 0 0 15 15

>1,2 - 1,5 10 1 10 1 0 0 2 0 24 24

>1,5 - 2 18 0 9 6 1 2 0 1 37 37

>2 - 3 8 1 3 0 3 1 1 0 17 17

>3 0 1 0 0 2 0 2 0 5 5

Figure 9. Income structure of surveyed areas in 2010 by occupation

0

2

4

6

8

10

12

14

16

18

20

≤ 0,9 >0,9 - 1,2 >1,2 - 1,5 >1,5 - 2 >2 - 3 >3

Fishermen

Fishfarmer

Fish General worker

Fishermen & Shop

Farmer general worker

Farmer & shop

Self Employe

Other

No of people per class

Mio. kyat

60

Table 28. Income/Expense distribution of surveyed areas

in 2010

Income/expenditure

classes incomes expenditures

(Mio Kyat)

no of

households/class

no of

households/class

≤ 0,9 2 17

>0,9 - 1,2 15 22

>1,2 - 1,5 24 16

>1,5 - 2 37 28

>2 - 3 17 13

>3 5 4

Figure 10. No. of households/ income-/expense-class

0

5

10

15

20

25

30

35

40

≤ 0,9 >0,9 -

1,2

>1,2 -

1,5

>1,5 - 2 >2 - 3 >3

Income distribution

expense distribution

income/expenditure classes

in Mio kyat

61

Table 29. Expense structure of surveyed areas in 2010 by occupation

Expense Fishermen

Fishermen

& Fishermen & Fishermen Farmer

Farmer

general Self

others Total

(Mio Kyat) farmer

general

worker & shop & shop Worker employment

HH %

≤ 0,9 8 2 5 1 0 1 0 0 17 17

>0,9 - 1,2 10 2 7 0 2 0 0 1 22 22

>1,2- 1,5 6 0 3 4 0 1 2 0 16 16

>1,5 - 2 13 1 8 3 1 1 1 0 28 28

>2 - 3 7 0 2 0 2 1 1 0 13 13

>3 0 1 1 0 1 0 1 0 4 4

Figure 11.Expense structure of surveyed areas in 2010 by occupation

0

2

4

6

8

10

12

14

≤ 0,9 >0,9 - 1,2 >1,2- 1,5 >1,5 - 2 >2 - 3 >3

Fishermen

Fishfarmer

Fish general worker

Fishermen & shop

Farmer & shop

Farmer general

worker

No of people per class

Mio. kyat

62

Table 30. Recorded fish species

No. Vernacular Name English Scientific name

1 nga-knonn-pa-dote hi fin barb Oreichthys Casuatis

2 nga-byet mud skipper Boleophthalmus boddarti

3 nga-zin-sat glass fish Parambasis ranga

4 nga-phe` feather back Notopterus notopterus

5 nga-la-bie Burmese river shad Gudusia variegata

6 nga-phe-aunn kind of carp Rohtee belengeri

7 nga-myit-chinn rohu Labeo rohita

8 nga-lone Burmese algae eater Crossocheilus burmanicas

9 nga-khone-ma swamp barb Puntius chola

10 nga-zin-yine striped dwarf catfish Mystus vittatus

11 nga-mhway Mastacembelus

12 nga-yant snake head murrel Channa striata

13 nga-gyaung giant catfish Aorichthys aori

14 nga-phaun-yoe garfish Xenentodon cancilla

15 nga-byay-ma climbing perch Anabas testudineus

16 nga-net-sein carp Labeo calabasu

17 nga-net-poke

Black

Sharkminnows. Labeo chrysophekadion

18 nga-gyee stinging catfish Heteropneustes fossilis

19 nga mway htoe kyarr zig-zag eel Mastacembelus armatus

20 nga-khue walking catfish Clarias batrachus

21 nga-nu-than pabo catfish Ompok pabo

22 nga shint ne swamp eel Monopterus albus

63

Table 31. No. of household classified by fishing gear in interview areas

Note: some households use more than 1 net type

No Village

Household

Net Freshwater

0.75"-1.0" 1.75"-2.0" 3.25"-4.0"- 4.5" 7.25" prawn trap

1 Shweletpan 2 10 12 3 3

2 Mamonkaing 2 4 9 2 0

3 Hepa 2 7 11 5 3

4 Nyaungbin 2 2 16 3 0

5 Lonton 4 3 7 5 0

Total 12 26 55 18 6

% 14.29 30.95 65.48 21.43 7.14

Table 32. Size of one gill net classified by different mesh size

0.75"-1.0" 1.75"-2.0" 3.25"-4.0"- 4.5" 7.25"

length =200 yard length= 102 Yard length= 130 yard length= 130 yard

depth= 3 yard depth= 4 yard depth= 12 yard depth= 12 yard

Table 33. Firewood consumption in the study area

No Village Household population

Consumption/ consumption/

household/year

(Tons)

person/year

(Tons)

1 Shweletpan 19 89 26.39 0.29

2 Mamonkaing 14 72 21.06 0.29

3 Hepa 22 124 38.54 0.31

4 Nyaungbin 27 153 54.22 0.35

5 Lonton 18 98 29.23 0.29

Total 100 536 169.44 0.32

64

Plate 3. House structures

Live in the boat on the lake

65

Plate 4. Some fishing gears and fish species

Featherback

Swamp Baarb

Prawn traps

Prawn traps

Small mesh size gill net

Measuring meshes of a net

66

CHAPTER 5: DISCUSSION

The Indawgyi lake sanctuary is a Ramsar Site and the most important bird area of Myanmar. The

lake environment, it´s soil, water, and the climate are suitable to grow rice, crops, vegetables and

fruits. A wide variety of flora and fauna resources remain in the area. These conditions forced a

permanent settlement growth leading to a relatively high population concentration within the past

20 years. Today´s lake area population density is 150 persons per km² - almost twice the average

population density of the country, which is 82 people/ km² (WHO, 2006).

The country wide number of individuals per family in rural areas is published to be 4.67

(Ministry of National Planning and Economic Development Myanmar, 2006). In the surveyed

areas an average household size of 5.4 members was recorded.

Contraceptives are not commonly available in government health centres. If at all, the private

sector is the sole source of contraception offerings. However private clinics are less likely to be

available in rural areas and where few international agencies are able to work, they face tight

restrictions on the use of permanent methods of family planning. (John Bercow (n.d.)).

The EC-Burma/ Myanmar Strategy Paper (2007-2013) also pointed out that the quality of public

health service is very low and the de facto introduction of user fees adds another hurdle

especially for the poor.

Despite the high population density, the Indawgyi area health infrastructure, with only 1 clinic

with one medical doctor for 45,000 people, was found significantly lower than published for the

balance of Myanmar.( 1 medical doctor per 2985 inhabitants, (WHO, 2004)). Whether this is the

result from an over proportional population growth rate, caused by immigration, a lack of family

67

planning, or from the before mentioned bureaucracy hurdles, is regardless. Most likely it is the

accumulation of all factors.

The life expectancy of Myanmar people is 61years for men and 67 years for woman (WHO,

2011). The Indawgyi lake area population falls behind. The age group above 61 counted only 13

persons (9 females and 4 males) out of 536.

For classification of a society Dr Devendra P Shresta, n.d. introduced the following raster:

“The economic active population can be categorized into employers, employees, self-employed

or own account workers, unpaid family workers and persons seeking employment for the first

time.”

The economically inactive population, on the other hand, includes children below the age of six,

persons retired from work, too old to work, or unable to work, persons able to work but neither

working nor looking for work. This large group includes females solely occupied with their own

household work, full- time school children, students and voluntarily idle persons. (Yin Yin Win,

2007 cited Hirashima, 1977).

Members of all of the above defined categories have been found among the population surveyed

in the 5 villages, Shweletpan, Mamonkaing, Hepa, Nyaungbin and Lonton. However the majority

of the economic active group were recorded as self-employed workers since most family

members regardless of sex participated in farming and fishing.

Farmers were mostly owners of land, but often of insufficient size to support the family

members. Only monsoon paddy cultivation is practiced in the surveyed areas. Even though Naing

Naing Latt, (2010) reported that most of the inhabitants of the Indawgyi lake area were engaged

in agriculture. 80% of the total population should make their living from agriculture. The result

68

of this survey proofs that only 5.78 % of the interviewees were farmer families, whilst 38.25% of

the families made their living mainly from fishing.

It would need further investigation to define if this discrepancy results from classification

differences, (some farmers work as fishers as well during the off season), the low percentage of

population interviewed (7.8% of the total population in the study area), if it is caused by the

chosen random sampling method, or if this study reflects more of the reality.

Generally, it must be admitted, that socioeconomic conditions are hard to analyse, as results of

interviews depend on the cooperation willingness of human beings and their characters, which

usually differ widely within the same community and from one community to another (M.A.

Abdrabo & M.A. Hassaan 2003). Some interviewees were willing to answer the questions

discovering their economic situation, others were not.

Household income is one of the most important determinants of welfare in a region. The ability

to meet basic needs, such as adequate food, clothing, sheltering and basic amenities, is largely

determined by the level of income. Poverty is often defined as the lack of resources to meet these

needs (CJ Meintjes, Development paper 145, Southern Africa, March 2001).

No distinct income correlation to occupation could be detected in the survey areas. Clear became,

according to the survey, 48% of total interviewees live below the World Bank defined poverty

index line (US$ 1.25 per person per day). As noticeable from the income per capita chart, the

inhabitants of Nyaungbin and Lonton enjoy slightly higher incomes as those living the others 3

villages. This result, however must be critically assessed as family size, which has been found as

main determinant for the living standard, is comparable if not higher than in the poorer”

villages”. Reason for the higher per capita income is the fact that the number of families falling

69

into the income classes 5 and 6 is apparently higher than in Sweletpan, Hepa and Mamonkaing.

(Appendix VI).

The indicative proxy indicators of poverty, as defined by the UNDP, which include basic factors

for wellbeing, such as access to farm land (food production), type of roofing system (shelter),

education level and health care facilities and sanitation (health) ( FAO,2003).

Applying these criteria, approximately 14% of interviewees are landless, and live in boats on the

lake. 66% of the houses in the survey area have grass/ palm thatch roofs, thus total 80% of

households fulfil at least one of the UNDP poverty indicators.

Looking at the availability of social services, such as health and education, the other indicators

for poverty, used by UNDP, the situation can be summarized as follows

Before 1960, in the Indawgyi Lake area the education standards were very low. People, who

wanted to attend middle or high school education, had to relocate to Mohnyin or other larger

cities. Between 1960 and 1988, the government enforced an anti-illiteracy campaign with the

target that all people should become literate. In consequence of this campaign, between 1988 and

1993, two state middle schools and 17 primary schools were established in the Indawgyi Lake

area. These were constructed and operated on self-help basis under the supervision of local

authorities. Teacher to pupil ratio was 1:50 in primary school level, 1:60 in middle school level

and 1:35 in high school level. (Naing Naing Latt, 2010).

During this study only 3.36% of the population was classified as illiterates. The student/teacher

ratios were found to be in the range defined by Naing Naing Latt in her work of 2010 or better.

An exceptional case was found in Nyaungbin where the teacher to pupil ratio was 1:100 in

middle school level. Primary level education is available for every village in the surveyed areas.

70

To get middle and high level education, school children from Shweletpan and Hepa have to visit

neighbour villages within a distance of 3 to 5 miles. Scholars from Nyaungbin and Mamonkaing

have to get over distances between 5 and 7 miles to benefit from high school level education.

After high school completion students can study in Mohnyin, Myitkyina (State capital) or

Mandalay Universities. It can be concluded, that the education offering in the area is more

satisfactorily than other criteria, like for example the health service infrastructure, as discussed

earlier in this chapter, for human well-being in the study area,

The provision of infrastructural services also plays an important role for the welfare of

households. Access to clean water and sanitation reduces mortality; access to transport provides

access to markets; access to electricity improves the living standards and saver food supply; it

also opens employment opportunities; telecommunications contributes to improvements in

economic activities and in living conditions.

In contrast, the non-provision of alleviates economic performance, since much time has to be

devoted to activities such as collecting fuel wood or clean water.- Time that could otherwise be

spent on income-earning activities (CJ Meintjes, Development paper 145, Southern Africa,

March 2001).

70% of Myanmar´s total population lives in rural areas (WHO, 2006). Only 10% of rural

households have access to electric power supply (Johannesburg Summit 2002). The surveyed

areas do not fall within these 10%, as the survey result proved.

In total 82% of all respondents depend on lake water for drinking and household whilst just 18%

are tube well users. . Considering the litter and other pollution brought uncontrolled into the lake,

it is dangerous to use lake water for drinking and cooking without treatment. In addition building

71

tube wells to the necessary depth (between 60 and 70 feet) is a difficult, costly and time

consuming task.

The HG concentration was reported to be 0,059 to 2,858ppm for the lake during the summers.

This exceeds the limit, set by the WHO (1ppb) significantly (> 200%). The nutrient

concentration, such as nitrate- nitrogen (0.096- 0.212) ppm and phosphate- phosphorus (0.034-

0.064) ppm indicate eutrophic conditions for the lake (Hla Hla Than, Dec 2006).

Reasons for the analysis results of water samples, taken during this study, which show neither

nitrate, nor phosphate, nor mercury, can be manifold. Probably the collection places chosen, a

relatively long storage period between sample collection and analysis and the season at the

sample draw caused the deviation from earlier measurements.

Therefore the statement, based on the results of the water analysis during this study, that the

surveyed areas are part of that 68% of the rural population, which have access to safe water (The

EC- Burma/ Myanmar Strategy Paper (2007- 2013) cited WHO report, 2004)) should be

critically reviewed.

The transportation infrastructure in Myanmar is relatively poor (Anthony Truong, Justin Tan,

2006). Light transportation such as buses and cars are a private sector activity in Myanmar. In the

surveyed areas 2 private owned cars serve as regular transportation alternative. During the wet

season the unpaved roads in the lake area hamper communication traffic seriously or even

prevent it. This issue exists despite the fact, that private efforts are undertaken to repair damaged

road sectors, because they are mandatory to facilitate the transportation of local products to the

market in towns.

72

Mobile phones were first introduced about 17 years ago (1994). In the beginning this technology

was only available to very few high ranking government officers and foreign diplomats. A few

years later, the government started selling CDMA mobile phones to the public. Those were

followed by GSM phones. The average density was 8 phones per one thousand inhabitants

(Today in Myanmar, Jan. 2009).

CDMA mobile phones were established in the surveyed areas in 2008. The costs were as high as

about 900,000 kyat per phone (= €900). During the interviews for this study, 5 phones per 536

inhabitants have been recorded. (2 phones however belong to one household). So the phone

density is statistically meeting the countries average.

Addressing the sustainability issue the following statements shall be used as guidelines.

To achieve a sustainable development, economic growth and environmental protection are

viewed as mutually comparable activities and not as conflicting ones (M.A. Abdrabo & M.A.

Hassaan 2003)

Environmental issues need to be carefully considered in the development of coastal and inland

aquaculture in Myanmar, paying close attention to environmental management of the sector will

not only provide a sound basis for sustainable development, but will also ensure continued

market access into importing markets that are becoming increasingly sensitive to environmental

concerns(FAO, 2003)

In Thailand the minimum mesh size designed for inland fisheries is set at 5 cm/ 2 inches

(stretched mesh), which allows the juveniles and sub-adults of many species to escape from the

gear (FAO, 2010). Myanmar freshwater fisheries law (1991) did not describe it. The result

showed that 14.29% of interviewees use smaller mesh size net (0.75"- 1").

73

By notification prohibited is the catching or keeping in capacity of spawners, breeders, and

fingerlings of freshwater fish in the months of May, June, July, and August (Aung Htay Oo,

2010).

Most people in the surveyed areas however work with their normal gear throughout the year.

14% of interviewees, who mostly live in boats on the lake pause for 2 months per year.

(Information derived from the answers on questions regarding their annual income).

Davies, Sebastian and Chan (2004) recorded 64 fish species in the lake basin. Local, Brang Gam

claimed that some fish which were popular and abound in the past have become rare (Irrawaddy

Magazine, Oct 2006).

During this study only 22 species were recorded. It needs further investigation, if this discrepancy

is caused by seasonal impacts or by diversity degradation. Answers from interviewees on

questions regarding their catch volume, support the fear that indeed a serious reduction of the fish

quantity and diversity in the lake has occurred over the past decade. Fishermen report that

nowadays their catch, using 27 nets equals the catch using 5 nets ten years ago.

Gold mining, “the boom and bust economic” causes great inequality and poverty in area, where

mining is taking place, prices for many goods and services have become inflationary. It also

creates numerous social problems, such as drug dependence and alcohol abuse, compulsive

gambling, malaria, and sexually transmitted diseases. Another serious issue is long term exposure

of workers to mercury. Often they handle mercury with their bare hands and spend long hours;

bare legged in mercury contaminated water. In addition local people lose their land due to gold

mining (Image Asia & Pan Kachin Development society (Nov.2004).

74

During the survey, above mentioned problems became not obvious, as they are long term issues.

But blocking of streams has been monitored and the potential risks, such as mercury

contamination can have happened unnoticeable in water and soil. Another reason was that the

surveyed villages are not part of the main gold mining area in the region. Only very few

interviewees were engaged in gold mining activity.

The fuel-efficient stove program conducted for Vietnam executed by Fauna & Flora International

recommended that using improved stoves for cooking meals can save 25% to 35% of fuel wood

compared to usage of traditional local stoves (Nguyen Hung Manh and Nguyen Phuong Thuy,

Aug 2009).

In the surveyed areas all households still use the traditional three legged stove and cook in open

air during the cold and dry season. The average total consumption of 100 household with 536

members was 169.44 tons per year. Considering that deforestation is one of the issues to achieve

sustainability in economic and ecologic developments and that especially a bird sanctuary needs

healthy forests this issue should be addressed.

75

CHAPTER 6: CONCLUSION AND RECOMMENDATION

The natural treasures of the Indawgyi Wildlife and Bird Sanctuary traditionally offered, and still

offer a variety of economic chances for the people living around the lake. These chances attract

immigrants and lead to an on-going population growth. The concomitant circumstances of

growing, unstructured population leads to pollution, increasing fresh water requirements and food

demand; are serious contingencies relating to a sustainable socio-ecologic development and

concurrent resource protection of this important wetland nature reserve.

In parallel the pressure on the eco-system and the underdeveloped infrastructure hamper the

chances for the inhabitants to structure solid bases for their families’ well-being. Overfishing and

limitations for successful farming, by the lack of irrigation systems form barriers to generate

better incomes, which leave margin to care about other, than the very basic needs to survive.

Under the given circumstances it is a challenge to develop higher environment awareness

amongst the population.

Besides these fundamental issues, the absence of social security systems in parallel to a poorly

developed health care infrastructure, as well as traditional minted thinking, that children are the

only way to secure the survival of the elder, lead to high birth-rates. As matter of fact, this

security thinking was partly true in the past. Today´s world however offers no longer enough

resources to support this model. So one of the less surprising results of this study was, family size

and per capita income, as one of the fundaments for human well-being, are counter proportional.

This reflects the fact, that the available resources for income generation are limited and will even

further decrease, if no counteractions are implemented.

76

A positive finding during the survey was the educational sector has significantly improved over

the past decade. All scholars today have access to basic and middle school education. Also high

school level education can be achieved without relocation. University grades can be obtained at

Mohnyin, Myitgyina and Mandalay. The limiting factors for more extensive use of the

educational offering are again the family incomes. However, better education is one of the

important keys to break the downward spiral, triggered by the before mentioned issues. It can

however be only one of the necessary measures to further support this sector.

Great affords are needed to improve the infrastructure as base for all other progress. This includes

in the first step the construction of roads, to enable transport of goods from the producer to the

consumer all year over. Paved roads will also support eco-touristic exploitation, which will be

discussed later, as a source of additional income.

Just as important is the need to supply electric power to the region and give access to it for all

inhabitants. This will ease the supply of freshwater from tube wells for the people and such

decrease health risks from lake water as cooking and drink water source. Electric supply will also

enable people to pump water from the lake and irrigate farmland on the fringe. So the harvests

can be improved, such increasing family incomes and reducing the needs to enlarge farmland

areas at the expense of protected forests.

To counter further degradation of fish diversity and density in the lake it will be indispensible to

install the necessary infrastructure and give it the power to control immigration and /or survey the

fishing activities. It is mandatory that the close seasons are strictly obeyed and fishing of

immature fish with tiny meshes is not practiced. Once further overfishing is stopped, measures to

recover the fish diversity should be implemented.

77

A controlled environment friendly touristic infrastructure would be an alternative to generate

additional income and compensate for losses caused by the before mentioned limitations for the

fishermen. An important positive side effect of such exploitation would be that the littering issue

which is a growing risk for the environment and as a consequence for the eco system service,

would get higher awareness of the producers as it lowers the attractiveness for tourists and have

direct impact on incomes.

Similar effects in regard to poison hunting may be expected from eco- tourism valorisation. If

locals continue to poison the birds and degrade the fauna diversity, less tourists will be attracted

to visit , lowering the chances of the involved to generate income.

To not be misunderstood, this is not a plea to open the doors for mass tourism like for example in

southern Thailand, which would destroy the fragile natural treasures. But the advantages of a

structured eco tourist approach are by far greater than the possible load on nature and it opens

opportunities for a sustainable socioeconomic development, which through other approaches

would be more difficult to reach.

To realize such a structured approach for a sustainable socioeconomic development of the

Indawgyi region, collaboration of all relevant stakeholders in the area, in the region, in the

country and also from the international community is mandatory. The experience of the past and

the economic situation of the country, which suffers from ineffective structures in many

government levels plus the constraints of many years under embargo from the western

hemisphere highlight the need of international engagement. This is not only in the interest of the

Myanmar people but also of the world, as natural treasures like the Indawgyi Nature Reserve

have become rare in today´s globalised world and their importance for the worldwide ecosystem

becomes more obvious with each natural disaster, the world is facing.

78

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http://www.blc-burma.org/html/myanmar%20law/lr_e_ml91_01.html (accessed 29.08.2011)

Telecommunication in Myanmar (n.d.),

http://www.myanmar2day.com/myanmar-information/2009/01/telecommunication-in-myanmar/

(accessed 29. 08.2011)

Burma (Myanmar) - Infrastructure, power, and communications (n.d.),

http://www.nationsencyclopedia.com/economies/Asia-and-the-Pacific/Burma-Myanmar-

INFRASTRUCTURE-POWER-AND-COMMUNICATIONS.html (accessed 29.08.2011)

Anthony Truong, Justin Tan (Dec, 2002), Rural Telecommunications Network Project Nothern

Myanmar

https://ccnet.stanford.edu/cgi-

bin/course.cgi?cc=ee244&action=handout_download&handout_id=ID11318645837934

(accessed 29.08.2011)

http://www.google.de/search?rlz=1C1SVED_enDE390DE390&sourceid=chrome&ie=UTF-8&q=family+planning+in+Myanmar

http://www.google.de/search?rlz=1C1SVED_enDE390DE390&sourceid=chrome&ie=UTF-8&q=family+planning+in+Myanmar

http://www.who.int/countries/mmr/en/

http://dyson.cornell.edu/research/researchpdf/wp/2001/Cornell_Dyson_wp0110.pdf

http://www.cbs.gov.np/Population/Monograph/Chapter%2009%20%20Trends,%20Patterns%20and%20Structure%20of%20Economically%20A.pdf

http://www.cbs.gov.np/Population/Monograph/Chapter%2009%20%20Trends,%20Patterns%20and%20Structure%20of%20Economically%20A.pdf

http://www.searo.who.int/en/Section313/Section1522_10916.htm

http://www.blc-burma.org/html/myanmar%20law/lr_e_ml91_01.html

http://www.myanmar2day.com/myanmar-information/2009/01/telecommunication-in-myanmar/

http://www.nationsencyclopedia.com/economies/Asia-and-the-Pacific/Burma-Myanmar-INFRASTRUCTURE-POWER-AND-COMMUNICATIONS.html

http://www.nationsencyclopedia.com/economies/Asia-and-the-Pacific/Burma-Myanmar-INFRASTRUCTURE-POWER-AND-COMMUNICATIONS.html

https://ccnet.stanford.edu/cgi-bin/course.cgi?cc=ee244&action=handout_download&handout_id=ID11318645837934

https://ccnet.stanford.edu/cgi-bin/course.cgi?cc=ee244&action=handout_download&handout_id=ID11318645837934

82

Appendix I. Population structure by gender and age of the study area

Age

≤ 5 6-10 11-15 16-20 21-25 26-30 31-35 36-40 41-45 46-50 51-55 56-60

≥

61 Total

Shweletpan

Total 24 12 7 5 10 8 8 6 2 3 3 0 1 89

Male 11 4 2 2 7 5 4 2 2 1 2 0 0 42

Female 13 8 5 3 3 3 4 4 0 2 1 0 1 47

Mamonkaing

Total 12 8 11 7 6 8 3 7 4 1 2 2 1 72

Male 6 4 5 3 2 5 1 4 3 0 1 0 0 34

Female 6 4 6 4 4 3 2 3 1 1 1 2 1 38

Hepa

Total 22 14 11 13 17 17 7 2 8 6 2 3 2 124

Male 13 6 6 4 9 10 5 1 5 1 0 3 0 63

Female 9 8 5 9 8 7 2 1 3 5 2 0 2 61

Nyaungbin

Total 24 28 13 12 12 24 6 8 5 3 10 2 6 153

Male 9 14 2 4 6 11 4 3 3 2 5 0 3 66

Female 15 14 11 8 6 13 2 5 2 1 5 2 3 87

Lonton

Total 20 11 10 9 8 9 12 4 4 1 6 1 3 98

Male 7 2 4 4 3 4 7 3 2 0 3 1 1 41

Female 13 9 6 5 5 5 5 1 2 1 3 0 2 57

Total

Total 102 73 52 46 53 66 36 27 23 14 23 8 13 536

% 19.03 13.62 9.70 8.58 9.89 12.31 6.72 5.04 4.29 2.61 4.29 1.49 2.43 100

Male 46 30 19 17 27 35 21 13 15 4 11 4 4 246

% 8.58 5.60 3.55 3.17 5.04 6.53 3.92 2.43 2.80 0.75 2.05 0.75 0.75 45.90

Female 56 43 33 29 26 31 15 14 8 10 12 4 9 290

% 10.45 8.02 6.16 5.41 4.85 5.78 2.80 2.61 1.49 1.87 2.24 0.75 1.68 54.10

83

Appendix II. Percentage distribution of literacy and educational status in the study area

ID Education Level Shweletpan

%

Mamonkaing

%

Hepa

%

Nyaungbin

%

Lonton

%

Total

%

1 Monastery 3.37 12.5 2.42 9.80 4.08 6.34

2 Primary (Attending) 17.98 16.67 11.29 20.26 15.31 16.42

3 Primary (Incomplete) 31.46 19.44 26.61 18.95 20.41 23.13

4 Middle (Attending) 4.49 4.17 7.26 5.88 4.08 5.41

5 Middle (Incomplete) 16.85 16.67 25.81 23.53 19.39 21.27

6 High (Attending) 1.12 6.94 0.80 1.31 5.10 2.61

7 High ( Incomplete) 2.25 6.94 0 3.92 4.08 3.17

8 Under graduate 0 0 1.61 1.96 2.04 1.31

9 Graduate 0 0 1.61 1.96 5.10 1.87

Literate 77.53 83.33 77.42 87.58 79.59 81.53

10 Illiterate 1.12 1.39 8.06 2.62 2.04 3.36

11 Young children 21.35 15.28 14.52 9.80 18.37 15.11

Total 100.00 100.00 100.00 100.00 100.00 100.00

84

Appendix III. Number of households and population by occupation

Occupation Category

Shw

elet

pan

Mam

onkai

ng

Hep

a

Nyau

ngbin

Lonto

n

Total


Fishermen 10 18 4 11 5 16 17 32 8 19 44 96 37.65

Fishermen & farmer 2 4 1 3 2 6 0 0 1 5 6 18 7.06

Fishermen & general worker 6 15 7 20 9 25 2 5 2 3 26 68 26.67

Fishermen & shop 0 0 2 4 4 12 1 5 1 2 8 23 9.02

Farmer & shop 0 0 0 0 1 3 2 7 3 8 6 18 7.06

Farmer & general worker 1 5 0 0 1 3 0 0 2 5 4 13 5.10

Self -employment 0 0 0 0 0 0 5 17 0 0 5 17 6.67

Others 0 0 0 0 0 0 0 0 1 2 1 2 0.78

Total 19 42 14 38 22 65 27 66 18 44 100 255 100

Note: % depends on working population

85

Appendix IV. Number of households and population by occupation

Occupation Category

Shw

elet

pan

Mam

onkai

ng

Hep

a

Nyau

ngbin

Lonto

n

Total


Fishermen 10 18 4 11 5 16 17 32 8 19 44 96 17.91

Fishermen & farmer 2 4 1 3 2 6 0 0 1 5 6 18 3.36

Fishermen & general worker 6 15 7 20 9 25 2 5 2 3 26 68 12.67

Fishermen & shop 0 0 2 4 4 12 1 5 1 2 8 23 4.29

Farmer & shop 0 0 0 0 1 3 2 7 3 8 6 18 3.36

Farmer & general worker 1 5 0 0 1 3 0 0 2 5 4 13 2.43

Self -employment 0 0 0 0 0 0 5 17 0 0 5 17 3.17

Others 0 0 0 0 0 0 0 0 1 2 1 2 0.37

Total 19 42 14 38 22 65 27 66 18 44 100 255 47.57

Note: % depends on total population

86

Appendix V. Income and expenses in surveyed areas in 2010

incomes and expenses in surveyed area in 2010 household in $ US - per head & poverty status Income classes in Mio Kyat

No Name

Fm

. Village Occupation

est. ann.

Inc. ann. exp. income exp. surpl.

HH

pov.inc. status ≤

0,9

>0.9 -

1.2

>1,2 -

1,5

>1,5

- 2

>2

- 3

>

3 size kyat Kyat $ US $ US $ US $ US

1 Chit Than 9 Shweletpan

Fish general

worker 1,544,125 1,507,500 2,161.78 2,110.50 51.27 4,106 under X

2 Zayar 5 Shweletpan fishermen 1,263,375 950,000 1,768.73 1,330.00 438.73 2,281 under X

3

Kyaw

Kyaw 5 Shweletpan

Fish general

worker 1,193,187 920,000 1,670.46 1,288.00 382.46 2,281 under X

4 Htun Win 4 Shweletpan fishermen 1,333,562 1,020,000 1,866.99 1,428.00 438.99 1,825 X

5

Maung

Zaw 4 Shweletpan fishermen 1,644,125 1,450,000 2,301.78 2,030.00 271.78 1,825 X

6

Aung

Naing Win 3 Shweletpan fishermen 1,200,500 650,000 1,680.70 910.00 770.70 1,369 X

7 Pho Pyar 6 Shweletpan fish farmer 1,403,750 1,090,000 1,965.25 1,526.00 439.25 2,738 under X

8

Kyaw

Myint 5 Shweletpan

Fish general

worker 1,499,000 1,290,000 2,098.60 1,806.00 292.60 2,281 under X

9 Pho Chin 4 Shweletpan fishermen 1,093,000 851,000 1,530.20 1,191.40 338.80 1,825 under X

10

Zaw

Khaing 4 Shweletpan fishermen 1,099,000 850,000 1,538.60 1,190.00 348.60 1,825 under X

11 San Lin 3 Shweletpan fishermen 1,125,000 930,000 1,575.00 1,302.00 273.00 1,369 X

12

Min Zaw

Oo 2 Shweletpan fishermen 1,443,750 1,204,000 2,021.25 1,685.60 335.65 913 X

13

Chit San

Mg 3 Shweletpan fishermen 1,403,750 735,000 1,965.25 1,029.00 936.25 1,369 X

14

Htun Htun

Naing 3 Shweletpan fishermen 1,270,000 792,000 1,778.00 1,108.80 669.20 1,369 X

15

Aung

Myint

Naing 5 Shweletpan fish farmer 1,125,000 945,000 1,575.00 1,323.00 252.00 2,281 under X

16 Htay Lwin 4

Mamonkain

g

fishermen &

shop 2,000,000 1,800,000 2,800.00 2,520.00 280.00 1,825 X

17 Ma Naing 5

Mamonkain

g

fish general

worker 1,600,000 1,290,000 2,240.00 1,806.00 434.00 2,281 under X

18 San Kyi 3

Mamonkain

g fishermen 2,000,000 1,680,000 2,800.00 2,352.00 448.00 1,369 x

19 Myint Win 5

Mamonkain

g

fish general

worker 1,500,000 1,195,000 2,100.00 1,673.00 427.00 2,281 under X

20

Aung

Maunn 5

Mamonkain

g fishermen 2,500,000 2,410,000 3,500.00 3,374.00 126.00 2,281 x

Fm = family, est. ann. Inc = estimate annual income, ann. exp. = annual expense, exp. = expense, surpl. = suplus, HH pov. Inc. = household poverty

income (number of household member x $ 1.25 x 365 days)

87


No Name Fm

. Village Occupation est. ann.


HH

pov.inc

. status ≤

0,9

>0.9 -

1.2

>1,2 -

1,5

>1,5

- 2

>2

- 3 >3

size kyat Kyat $ US $ US $ US $ US

21 Ba Wai 5

Mamonkain

g

fish general

worker 1,800,000 1,790,000 2,520.00 2,506.00 14.00 2,281 X

22 Aung Lwin 8

Mamonkain

g

Fish general

worker 1,250,000 965,000 1,750.00 1,351.00 399.00 3,650 under X

23 Aung Aung 3

Mamonkain

g

Fish general

worker 1,263,300 880,000 1,768.62 1,232.00 536.62 1,369 X

24 Tin Soe 4

Mamonkain

g

fishermen &

shop 1,200,000 899,000 1,680.00 1,258.60 421.40 1,825 under X

25

Win

Maung 7

Mamonkain

g fishermen 2,200,000 2,470,000 3,080.00 3,458.00 -378.00 3,194 under x

26 Soe Naing 6

Mamonkain

g fish famer 2,073,000 1,730,000 2,902.20 2,422.00 480.20 2,738 x

27 Pho Si 5

Mamonkain

g

Fish general

worker 1,150,000 940,000 1,610.00 1,316.00 294.00 2,281 under X

28 Pho Si 5

Mamonkain

g

Fish general

worker 2,000,000 2,100,000 2,800.00 2,940.00 -140.00 2,281 X

29 Aung Than 7

Mamonkain

g fishermen 1,650,000 1,600,000 2,310.00 2,240.00 70.00 3,194 under X

30

Thein

Aung 6 Hepa

fish general

worker 1,400,000 1,090,000 1,960.00 1,526.00 434.00 2,738 under X

31 Min Yi 5 Hepa

Fish general

worker 1,800,000 1,600,000 2,520.00 2,240.00 280.00 2,281 X

32 Than Kyaw 8 Hepa fishermen 1,810,000 1,725,000 2,534.00 2,415.00 119.00 3,650 under X

33 Kalar 5 Hepa

Fish general

worker 1,500,000 1,405,000 2,100.00 1,967.00 133.00 2,281 under X

34 Ko Oo 8 Hepa

fishermen &

shop 1,450,000 1,330,000 2,030.00 1,862.00 168.00 3,650 under X

35 Min Lwin 7 Hepa

Fish general

worker 2,300,000 2,290,000 3,220.00 3,206.00 14.00 3,194 x

36 Myo Chit 5 Hepa

fishermen &

shop 2,000,000 1,510,000 2,800.00 2,114.00 686.00 2,281 X

37 Win Hlaing 9 Hepa

Fish general

worker 1,800,000 1,725,000 2,520.00 2,415.00 105.00 4,106 under X

38 Tin Nyunt 3 Hepa fishermen 1,200,000 1,172,000 1,680.00 1,640.80 39.20 1,369 X

39 Win Than 7 Hepa fishermen 2,400,000 2,470,000 3,360.00 3,458.00 -98.00 3,194 x

40

Soe Myint

Naing 8 Nyaungbin

fishermen &

shop 1,900,000 1,820,000 2,660.00 2,548.00 112.00 3,650 under X

88


No Name Fm. Village Occupation est. ann. Inc. ann. exp. income exp. surpl. HH pov.inc. status ≤

0,9

>0.9 -

1.2

>1,2 -

1,5

>1,5-

2

>2

- 3 >3


41

Htay

Lwin 4 Nyaungbin fishermen 1,840,000 1,940,000 2,576.00 2,716.00 -140.00 1,825 X

42 U Moe 4 Nyaungbin fishermen 1,000,000 806,000 1,400.00 1,128.40 271.60 1,825 under X

43 Mg Mg 8 Nyaungbin fishermen 1,200,000 1,185,000 1,680.00 1,659.00 21.00 3,650 under X

44

Tun

Shwe 5 Nyaungbin fishermen 1,250,000 1,186,000 1,750.00 1,660.40 89.60 2,281 under X

45 Sein Win 5 Nyaungbin fishermen 1,150,000 903,000 1,610.00 1,264.20 345.80 2,281 under X

46 Thet Tin 3 Nyaungbin fishermen 1,500,000 1,471,000 2,100.00 2,059.40 40.60 1,369 X

47 Nay Lin 7 Nyaungbin fishermen 1,510,000 1,460,000 2,114.00 2,044.00 70.00 3,194 under X

48

Than

Win 7 Nyaungbin fishermen 2,650,000 2,760,000 3,710.00 3,864.00 -154.00 3,194 x

49 Tun Thin 4 Nyaungbin fishermen 1,800,000 1,700,000 2,520.00 2,380.00 140.00 1,825 X

50

Aung

Than 8 Nyaungbin

Fish general

worker 2,500,000 3,014,000 3,500.00 4,219.60 -719.60 3,650 under x

51

Zaw Win

Tun 6 Nyaungbin fishermen 2,400,000 2,830,000 3,360.00 3,962.00 -602.00 2,738 x

52 Htay Win 4 Nyaungbin fishermen 2,550,000 2,790,000 3,570.00 3,906.00 -336.00 1,825 X

53

Kyaw

Aye 3 Nyaungbin

Fish general

worker 1,800,000 1,687,000 2,520.00 2,361.80 158.20 1,369 X

54

Saw

Naing 4 Nyaungbin fishermen 2,000,000 1,920,000 2,800.00 2,688.00 112.00 1,825 X

55

Nyunt

Lwin 6 Nyaungbin fishermen 1,900,000 1,840,000 2,660.00 2,576.00 84.00 2,738 under X

56

Aung Ko

Win 6 Nyaungbin fishermen 1,750,000 1,565,000 2,450.00 2,191.00 259.00 2,738 under X

57 Htay Win 6 Nyaungbin fishermen 1,250,000 1,020,000 1,750.00 1,428.00 322.00 2,738 under X

58 Pho Than 4 Nyaungbin fishermen 1,500,000 1,256,000 2,100.00 1,758.40 341.60 1,825 X

59 Soe Lin 5 Nyaungbin fishermen 1,840,000 1,465,000 2,576.00 2,051.00 525.00 2,281 X

60

Kyaw

Phe 10 Lonton fish farmer 3,200,000 3,092,000 4,480.00 4,328.80 151.20 4,563 under x

89


No Name Fm. Village Occupation est. ann. Inc. ann. exp. income exp. surpl.

HH

pov.inc. status ≤

0,9

>0.9 -

1.2

>1,2 -

1,5

>1,5-

2

>2

- 3 >3


61 Myo Htet 10 Lonton

Fish general

worker 2,100,000 1,892,000 2,940.00 2,648.80 291.20 4,563 under x

62 Tun Tun 3 Lonton fishermen 1,800,000 1,596,000 2,520.00 2,234.40 285.60 1,369 X

63 Than Tun 4 Lonton fishermen 1,700,000 694,000 2,380.00 971.60 1,408.40 1,825 X

64

Aung

Aung 7 Lonton fishermen 2,100,000 1,875,000 2,940.00 2,625.00 315.00 3,194 under X

65

Tin Aung

San 5 Lonton fishermen 2,000,000 1,580,000 2,800.00 2,212.00 588.00 2,281 X

66 San Kyaw 4 Lonton

Fish general

worker 1,300,000 984,000 1,820.00 1,377.60 442.40 1,825 under X

67 Win Bo 6 Lonton fishermen 2,500,000 2,006,000 3,500.00 2,808.40 691.60 2,738 x

68

Nay Myo

Aung 3 Lonton fishermen 1,600,000 980,000 2,240.00 1,372.00 868.00 1,369 X

69

U Htwe

Mg 8 Shweletpan

fish general

worker 1,685,125 1,576,000 2,359.18 2,206.40 152.78 3,650 under X

70

U Thaung

Nyunt 2 Shweletpan

fish general

worker 1,700,000 1,627,000 2,380.00 2,277.80 102.20 913 X

71

U Htay

Maung 4 Shweletpan

fish general

worker 1,350,000 623,000 1,890.00 872.20 1,017.80 1,825 X

72 Daw Htoo 10 Shweletpan

farmer

general

worker 1,916,000 1,848,000 2,682.40 2,587.20 95.20 4,563 under X

73 A Mg Gyi 6 Hepa fishermen 2,000,000 1,627,500 2,800.00 2,278.50 521.50 2,738 X

74

Myo

Naing 4 Hepa

Fish general

worker 900,000 599,900 1,260.00 839.86 420.14 1,825 under X

75

Ma Mya

htwe 6 Hepa fish farmer 1,000,000 715,700 1,400.00 1,001.98 398.02 2,738 under X

76

Ko Than

Tun Oo 4 Hepa

Fish general

worker 1,365,000 845,000 1,911.00 1,183.00 728.00 1,825 X

77

Ko Tun

Tun 4 Hepa fishermen 1,100,000 797,000 1,540.00 1,115.80 424.20 1,825 under X

78

Ko Aye

Ko 5 Hepa

Fish general

worker 1,050,000 854,000 1,470.00 1,195.60 274.40 2,281 under X

79

Ko Myint

San 3 Hepa

Fish general

worker 1,400,000 928,500 1,960.00 1,299.90 660.10 1,369 X

80

Ko Moe

Win 4 Hepa fish farmer 1,000,000 686,020 1,400.00 960.43 439.57 1,825 under X

90


No Name Fm.

Village Occupation est. ann.


HH

pov.inc

. status

≤

0,9

>0.9 -

1.2

>1,2 -

1,5

>1,5-

2

>2

- 3 >3


81

Ko Thet

Sein 5 Hepa

fishermen &

shop 1,623,500 1,293,500 2,272.90 1,810.90 462.00 2,281 under X

82 Ko Tin Tun 7 Hepa

fishermen &

shop 1,547,900 1,307,900 2,167.06 1,831.06 336.00 3,194 under X

83 Ma Ya Min 6 Hepa

farmer general

worker 2,244,000 1,405,600 3,141.60 1,967.84 1,173.76 2,738 x

84

Moe moe

San 7 Hepa farmer & shop 4,260,900 2,869,300 5,965.26 4,017.02 1,948.24 3,194 x

85 Maung Pye 4 Lonton fishermen 2,000,000 1,669,000 2,800.00 2,336.60 463.40 1,825 X

86

San Naing

Win 3 Lonton fishermen 1,925,000 1,150,500 2,695.00 1,610.70 1,084.30 1,369 X

87

Kyaw

Naing Win 4 Lonton

fishermen &

shop 1,905,000 1,462,500 2,667.00 2,047.50 619.50 1,825 X

88 Daw Chaw 5 Lonton farmer & shop 2,920,000 2,205,000 4,088.00 3,087.00 1,001.00 2,281 x

89 Mat Naw 5 Lonton

farmer general

worker 848,800 594,000 1,188.32 831.60 356.72 2,281 under X

90

Daw Toe

Sein 10 Lonton farmer & shop 1,503,000 1,186,500 2,104.20 1,661.10 443.10 4,563 under X

91

U Wai Moe

Tun 3 Lonton other 1,920,000 1,002,500 2,688.00 1,403.50 1,284.50 1,369 X

92

Daw Si Si

Naing 7 Lonton

farmer general

worker 1,557,100 2,214,000 2,179.94 3,099.60 -919.66 3,194 under X

93 U Nay Win 5 Lonton farmer & shop 2,012,000 1,076,500 2,816.80 1,507.10 1,309.70 2,281 x

94

U San

Shwe 9

Nyaungbi

n self employment 4,508,000 2,408,000 6,311.20 3,371.20 2,940.00 4,106 x

95 Ah Yin 7

Nyaungbi

n farmer & shop 2,015,000 1,695,000 2,821.00 2,373.00 448.00 3,194 under X

96

Aung

Kyaw

Myint 6

Nyaungbi

n self employment 1,390,000 1,373,200 1,946.00 1,922.48 23.52 2,738 under X

97

Kyaw San

Win 8

Nyaungbi

n farmer & shop 5,790,000 3,362,004 8,106.00 4,706.81 3,399.19 3,650 x

98

Daw Khin

Nyo 9

Nyaungbi

n self employment 7,350,000 3,669,000 10,290.00 5,136.60 5,153.40 4,106 x

99 U Soe Win 3

Nyaungbi

n self employment 1,460,000 1,435,000 2,044.00 2.009,00 35.00 1,369 X

100

Ko Thet

Zaw 4

Nyaungbi

n self employment 3,000,000 1,560,000 4,200.00 2,184.00 2,016.00 1,825 X

91

Appendix VI. Per capita income and average household members by village

Sweletpan Mamonkaing Hepa Nyaungbin Lonton

income* members** income* members** income* members** income* members** income* members**

( Kyat) ( Kyat) (Kyat) (Kyat)

295,418 4.68 335,921 5.1 299,607 5.6 397,405 5.67 356,030 5.44

* income per household member

** members per household

Note: income per capital 50.000 means 50,000 kyats and so on…

0

50.000

100.000

150.000

200.000

250.000

300.000

350.000

400.000

450.000

Sweletpan

income/ capita

Mamonkaing

Haepa/Hepa

Nyaungbin

Lonton 0

1

2

3

4

5

6

Sweletpan

members/ household

Sweletpan

Mamonkain

Haepa/ Hepa

Nyaungbin

Lonton

92

Appendix VI a. Economy breakdown by village in 2010 Shweletpan

sample size total Income

av.HH

Income

no. Households per income class ( Mio Kyat)

(annual) (annual)

class 1 class 2 class 3 class 4 class 5 class6

Kyat Kyat

≤ 0,9 >0,9 to 1,2 >1,2 to 1,5 >1,5 to 2 >2 to 3 > 3

total no. of households 97

total no. of inhabitants: 337 26.41%

interviewed:

household(s) 19 26,292,249.0 1,383,802.6

0 5 9 5 0 0

inhabitant(s) 89 295,418.5

(3f,1fw,1ff)

(6f,2fw,1ff) (1f,3fw,1faw)

av. Inhab. / household 4.68

legend: f = fisherman

av. Inhab. = average

inhabitant

fw= fish general worker

fs= fisher plus shop

ff= fishfarmer

faw= farm general worker

fas= farmer plus shop

Notes:

se= self empoyed The common international poverty line has in the past been roughly $1 a day. (Sachs, Jeffrey D. The End of Poverty

2005).

In 2008, the World Bank came out with a revised figure of $1.25 at 2005 purchasing-power parity (PPP).[The World Bank Economic Review, 23, 2, 2009, pp. 163-184]

Converted into kyat ( 1 US $= 715kyat) and calculated per year (365 days) - kyat per inhabitant 326,219

Findings:

The average income of inhabitants of Sweletpan is almost 10% below the world bank poverty line (295,418kyat/ 326,219 kyat).

The no of members per household has stronger impact on poverty than the absolute household income (appendix v)

Actually 47.36% of all households of Shweletpan (9) have high enough incomes to excess the poverty line for their members. (appendix v)

No Swetlapan household incomes fall in the higher categories 2to 3 mio or above 3 mio kyat.

No distinct income correlation to occupation can be

detected.

All households earn more than they spend. The annual saving amounts in 2010 were between US $ 50 to 1000. (appendix v, surplus)

93

Appendix VI b. Economy breakdown by village in 2010 Mamonkaing

sample

size total Income

av.HH

Income


(annual) (annual)


Kyat Kyat

≤ 0,9 mio >0,9 to 1,2 >1,2 to 1,5 >1,5 to 2 >2 to 3 > 3



interviewed:

household(s) 14 24,186,300.0 1,727,592.9

0 2 3 6 3 0


(1fs,1fw) (3fw) (2f,3fw,1fs) (2f,1ff,)





ff= fishfarmer



Notes:

se= self empoyed

The common international poverty line has in the past been roughly $1 a day. (Sachs, Jeffrey D. The End of Poverty 2005)

In 2008, the World Bank came out with a revised figure of $1.25 at 2005 purchasing-power parity (PPP).[The World Bank Economic Review, 23, 2, 2009,

pp. 163-184]

Converted into kyat ( 1 US $= 715 kyat) and calculated per year (365 days) - kyat per inhabitant 326,219

Findings: (assuming the low % of total population interviewed, can be utilized to deliver meaningful

results)

The average income of inhabitants of Mamonkaing is slightly above the world bank poverty line (335,920 kyat/ 326,219 kyat). The higher no of members per households as compared to Sweletpan results in slightly more poor households, although the incomes are significantly

higher

Actually 50% of all households of Mamonkaing (7) have high enough incomes to excess the poverty line for their members.

(appendix v)

The average income per household is almost 25% above that of the Sweletpan households Two Mamonkaing households with 7 members and 2.2 mio kyat income and with 5 members and 2 mio kyat income respectively had higher expenditures

than income

No distinct income correlation to occupation can be

detected.

The annual saving amounts in 2010 except for the 2 deficit households were between US $ 14 to 536. (appendix v)

94

Appendix VI c. Economy breakdown by village in 2010 Hepa

sample size total Income av.HH Income


(annual) (annual)


Kyat Kyat

≤ 0,9 mio >0,9 to 1,2 >1,2 to 1,5 >1,5 to 2 >2 to 3 > 3



interviewed:

household(s) 22 37,151,300.0 1,688,695.5

1 5 5 7 3 1


1fw 2f,1fw,2ff 1fs,4fw (2f,2fw,3fs,) 1f,1fw,1faw 1fas





ff= fishfarmer



Notes:

se= self empoyed

The common international poverty line has in the past been roughly $1 a day. (Sachs, Jeffrey D. The End of Poverty

2005)


Converted into Kyat ( 1 US $= 715 kyat) and calculated per year (365 days) - kyat per inhabitant 326,219

Findings:

The average income of inhabitants of Hepa (299,607 kyat) is about the same as in Sweletpan, about 8% below the world bank poverty line (299,607 kyat/ 326,219 kyat).

Hepa households have a high average family member number

(5.6)

Actually 45.45% of all households of Hepa (10) have high enough incomes to excess the poverty line for their members. (appendix v) The average income per household (1,688,695 Kyat) is approximately 22% above that of the Sweletpan

households

One Hepa household with 7 members and 2.4 mio kyat income had slightly higher expenditures than income (US$ 98 -kyat 70,560)

No distinct income correlation to occupation can be detected.

The annual saving amounts in 2010 except for the1 deficit household were between US $ 14 to 1,948.

(appendix v, surplus)

95

Appendix VI d. Economy breakdown by village in 2010 Nyaungbin

sample size total Income

av. HH

Income


(annual) (annual)

class

1 class 2 class 3 class 4 class 5 class6

Kyat Kyat

≤ 0,9 >0,9 to 1,2 >1,2 to 1,5 >1,5 to 2 >2 to 3 > 3



interviewed:

household(s) 27 60,803,000.0 2,251,963.0

0 3 6 9 6 3


3f 4f,2se 7f,1fs,1fw 3f,1fw,1fas,1se 1fas,2se





ff= fishfarmer



Notes:

se= self employed


In 2008, the World Bank came out with a revised figure of $1.25 at 2005 purchasing-power parity (PPP).[The World Bank Economic Review, 23, 2, 2009, pp. 163-

184]

Converted into Kyat ( 1 US $= 715 kyat) and calculated per year (365 days) - kyat per inhabitant 326,219

Findings:

The average income of inhabitants of Nyaungbin (397,405 kyat) is about 22% above the world bank poverty line (397,405 kyat/ 326,219 kyat).

Nyaungbin households have about the same average family member number( 5.67) than Hepa households

Despite the high level of household incomes, only 55.56% of households earn more than the individual’s poverty line level, due to high

member numbers (appendix v)

The average income per household (2,251,963Kyat) is approximately 35% above that of the lowest (Sweletpan) households

5 of the Nyaungbin Households had higher expenses than incomes, 3 of them significantly (= > 10% above income). No distinct income correlation to occupation can be detected, even though self- employed contributed over

proportional to the village average income.

The annual saving amounts in 2010 were between US $ 21to >5000. (appendix v, surplus)

96

Appendix VI e. Economy breakdown by village in 2010 Lonton

sample

size total Income aver. Income


(annual) (annual)

class

1 class 2 class 3 class 4 class 5 class6

Kyat Kyat

≤ 0,9 >0,9 to 1,2 >1,2 to 1,5 >1,5 to 2 >2 to 3 > 3



interviewed:

household(s) 18 34,890,900.0 1,938,383.3

1 0 1 10 5 1


1faw 1fw (6f,1fs,1fas,1faw,1o) 2f, 1fw,2fas 1ff



fw= fish general

worker


ff= fish farmer



se= self employed

Notes:

o= other



Converted into kyat ( 1 US $= 715 kyat) and calculated per year (365 days) - kyat per inhabitant 326,219

Findings:

The average income of inhabitants of Lonton (356,029 kyat) is 9% above the world bank poverty line (356,029kyat / 326,219 kyat).

Lonton households have an average household member number of 5.44.

Actually 61.11% (11) of all households in Lonton have high enough incomes to excess the poverty line for their members. (appendix v)

The average income per household (1,938,383 kyat) is approximately 40% above that of the lowest (Sweletpan) households

1 Lonton household has higher expenses than income (40%)

No distinct income correlation to occupation can be detected.

The annual saving amounts in 2010 except for the1 deficit household were between US $ 151 to 1408. (appendix v, surplus)

97

Appendix VII. Expenses in surveyed area in 2010

Expenses in surveyed area in 2010 expense classes by occupation

No Name

Fm

. Village Occupation ann. exp. ≤

0,9

>0.9 -

1.2

>1,2 -

1,5

>1,5-

2

>2 -

3 >3

size kyat

1 Chit Than 9 Shweletpan Fish general worker 1,507,500 X

2 Zayar 5 Shweletpan fishermen 950,000 X

3 Kyaw Kyaw 5 Shweletpan Fish general worker 920,000 X

4 Htun Win 4 Shweletpan fishermen 1,020,000 X

5 Maung Zaw 4 Shweletpan fishermen 1,450,000 X

6 Aung Naing Win 3 Shweletpan fishermen 650,000 X

7 Pho Pyar 6 Shweletpan fish farmer 1,090,000 X

8 Kyaw Myint 5 Shweletpan Fish general worker 1,290,000 X

9 Pho Chin 4 Shweletpan fishermen 851,000 X

10 Zaw Khaing 4 Shweletpan fishermen 850,000 X

11 San Lin 3 Shweletpan fishermen 930,000 X

12 Min Zaw Oo 2 Shweletpan fishermen 1,204,000 X

13 Chit San Mg 3 Shweletpan fishermen 735,000 X

14 Htun Htun Naing 3 Shweletpan fishermen 792,000 X

15

Aung Myint

Naing 5 Shweletpan fish farmer 945,000 X

16 Htay Lwin 4 Mamonkaing fishermen & shop 1,800,000 X

17 Ma Naing 5 Mamonkaing fish general worker 1,290,000 X

18 San Kyi 3 Mamonkaing fishermen 1,680,000 X

19 Myint Win 5 Mamonkaing fish general worker 1,195,000 X

20 Aung Maunn 5 Mamonkaing fishermen 2,410,000 X

21 Ba Wai 5 Mamonkaing fish general worker 1,790,000 X

22 Aung Lwin 8 Mamonkaing Fish general worker 965,000 X

23 Aung Aung 3 Mamonkaing Fish general worker 880,000 X

24 Tin Soe 4 Mamonkaing fishermen & shop 899,000 X

25 Win Maung 7 Mamonkaing fishermen 2,470,000 X

26 Soe Naing 6 Mamonkaing fish famer 1,730,000 X

27 Pho Si 5 Mamonkaing Fish general worker 940,000 X

28 Pho Si 5 Mamonkaing Fish general worker 2,100,000 X

29 Aung Than 7 Mamonkaing fishermen 1,600,000 X

30 Thein Aung 6 Hepa fish general worker 1,090,000 X

31 Min Yi 5 Hepa Fish general worker 1,600,000 X

32 Than Kyaw 8 Hepa fishermen 1,725,000 X

98


No Name

Fm.

Village Occupation ann. exp. ≤

0.9

0.9 <

1.2

1,2 <

1,5

1,5 <

2

2 <

3 3+ Siz

e kyat

33 Kalar 5 Hepa Fish general worker 1,405,000 X

34 Ko Oo 8 Hepa fishermen & shop 1,330,000 X

35 Min Lwin 7 Hepa Fish general worker 2,290,000 X

36 Myo Chit 5 Hepa fishermen & shop 1,510,000 X

37 Win Hlaing 9 Hepa Fish general worker 1,725,000 X

38 Tin Nyunt 3 Hepa fishermen 1,172,000 X

39 Win Than 7 Hepa fishermen 2,470,000 X

40

Soe Myint

Naing 8 Nyaungbin fishermen & shop 1,820,000 X

41 Htay Lwin 4 Nyaungbin fishermen 1,940,000 X

42 U Moe 4 Nyaungbin fishermen 806,000 X

43 Mg Mg 8 Nyaungbin fishermen 1,185,000 X

44 Tun Shwe 5 Nyaungbin fishermen 1,186,000 X

45 Sein Win 5 Nyaungbin fishermen 903,000 X

46 Thet Tin 3 Nyaungbin fishermen 1,471,000 X

47 Nay Lin 7 Nyaungbin fishermen 1,460,000 X

48 Than Win 7 Nyaungbin fishermen 2,760,000 X

49 Tun Thin 4 Nyaungbin fishermen 1,700,000 X

50 Aung Than 8 Nyaungbin Fish general worker 3,014,000 X

51 Zaw Win Tun 6 Nyaungbin fishermen 2,830,000 X

52 Htay Win 4 Nyaungbin fishermen 2,790,000 X

53 Kyaw Aye 3 Nyaungbin Fish general worker 1,687,000 X

54 Saw Naing 4 Nyaungbin fishermen 1,920,000 X

55 Nyunt Lwin 6 Nyaungbin fishermen 1,840,000 X

56 Aung Ko Win 6 Nyaungbin fishermen 1,565,000 X

57 Htay Win 6 Nyaungbin fishermen 1,020,000 X

58 Pho Than 4 Nyaungbin fishermen 1,256,000 X

59 Soe Lin 5 Nyaungbin fishermen 1,465,000 X

60 Kyaw Phe 10 Lonton fish farmer 3,092,000 X

61 Myo Htet 10 Lonton Fish general worker 1,892,000 X

62 Tun Tun 3 Lonton fishermen 1,596,000 X

63 Than Tun 4 Lonton fishermen 694,000 X

64 Aung Aung 7 Lonton fishermen 1,875,000 X

65 Tin Aung San 5 Lonton fishermen 1,580,000 X

66 San Kyaw 4 Lonton Fish general worker 984,000 X

67 Win Bo 6 Lonton fishermen 2,006,000 X

99


No Name Fm.

Village Occupation ann. exp. ≤

0.9

0.9 <

1.2

1,2 <

1,5

1,5 <

2

2 <

3

3

+. size kyat

68 Nay Myo Aung 3 Lonton fishermen 980,000 X

69 U Htwe Mg 8

Shweletpa

n fish general worker 1,576,000 X

70 U Thaung Nyunt 2

Shweletpa

n fish general worker 1,627,000 X

71 U Htay Maung 4

Shweletpa

n fish general worker 623,000 X

72 Daw Htoo 10

Shweletpa

n farmer general worker 1,848,000 X

73 A Mg Gyi 6 Hepa fishermen 1,627,500 X

74 Myo Naing 4 Hepa Fish general worker 599,900 X

75 Ma Mya htwe 6 Hepa fish farmer 715,700 X

76 Ko Than Tun Oo 4 Hepa Fish general worker 845,000 X

77 Ko Tun Tun 4 Hepa fishermen 797,000 X

78 Ko Aye Ko 5 Hepa Fish general worker 854,000 X

79 Ko Myint San 3 Hepa Fish general worker 928,500 X

80 Ko Moe Win 4 Hepa fish farmer 686,020 X

81 Ko Thet Sein 5 Hepa fishermen & shop 1,293,500 X

82 Ko Tin Tun 7 Hepa fishermen & shop 1,307,900 X

83 Ma Ya Min 6 Hepa farmer general worker 1,405,600 X

84 Moe moe San 7 Hepa farmer & shop 2,869,300 X

85 Maung Pye 4 Lonton fishermen 1,669,000 X

86 San Naing Win 3 Lonton fishermen 1,150,500 X

87

Kyaw Naing

Win 4 Lonton fishermen & shop 1,462,500 X

88 Daw Chaw 5 Lonton farmer & shop 2,205,000 X

89 Mat Naw 5 Lonton farmer general worker 594,000 X

90 Daw Toe Sein 10 Lonton farmer & shop 1,186,500 X

91 U Wai Moe Tun 3 Lonton other 1,002,500 X

92 Daw Si Si Naing 7 Lonton farmer general worker 2,214,000 X

93 U Nay Win 5 Lonton farmer & shop 1,076,500 X

94 U San Shwe 9 Nyaungbin self employment 2,408,000 X

95 Ah Yin 7 Nyaungbin farmer & shop 1,695,000 X

96

Aung Kyaw

Myint 6 Nyaungbin self employment 1,373,200 X

97 Kyaw San Win 8 Nyaungbin farmer & shop 3,362,004 X

98 Daw Khin Nyo 9 Nyaungbin self employment 3,669,000 X

99 U Soe Win 3 Nyaungbin self employment 1,435,000 X

100 Ko Thet Zaw 4 Nyaungbin self employment 1,560,000 X